Financial stability review. May 2024.
Date: 2024-06-14
Institutions: European Central Bank
Subjects: economic recovery, euro area, financial institution, financial stability, monetary policy, serial publication, stability programme

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May 2024 

 
 
 
 
 
 
Contents 

Foreword 

Overview 

1 

Macro-financial and credit environment 

1.1  While risks of a deep recession have declined, geopolitical risks 

are on the rise 

1.2 

Lax fiscal policies may reinforce public debt sustainability 
concerns 

1.3  Euro area firms are coping with rising debt service costs 

Box 1 Corporate debt service and rollover risks in an environment of 

higher interest rates 

1.4  Strong labour markets support household resilience 

1.5  Correction under way in property markets, notably the 

commercial segment 

2 

Financial markets 

2.1  Markets adjust to expected shift in monetary policy 

2.2  Benign pricing of risk keeps asset prices vulnerable to shocks 

Box 2 Low implied equity market volatility could underestimate financial 

stability vulnerabilities 

2.3  Exogenous risks could add to volatility in euro area markets 

Box 3 Financial stability risks from basis trades in the US Treasury and 

euro area government bond markets 

3 

Euro area banking sector 

3.1  Profitability peaked at multi-year highs as headwinds to income 

strengthen 

3.2  Bank funding costs have continued to increase 

3.3  Asset quality is slowly deteriorating, with commercial real estate 

and low provisioning levels most concerning 

3.4  Resilient banks amid subdued market valuations 

Box 4 Non-bank financial intermediaries as providers of funding to euro 

area banks 

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4 

Non-bank financial sector 

4.1 

4.2 

Fragile macro-outlook may still test non-banks’ resilience 

Funds face risks from concentrated portfolios, real estate and low 
liquidity 

Box 5 Assessing the liquidity preparedness of investment funds to meet 

margin calls in derivatives markets 

4.3  Strong solvency but uncertain profitability outlook for insurers 

5 

Macroprudential policy issues 

5.1  Preserve banking sector resilience and enhance the 

macroprudential framework for banks 

5.2  Progress towards a capital markets union requires a solid 

institutional and policy framework for non-banks 

5.3  Other ongoing policy initiatives that support euro area financial 

stability 

Box 6 Containing risks from leverage in the NBFI sector – insights from 

recent policy initiatives 

Special Features 

A 

B 

C 

Turbulent times: geopolitical risk and its impact on euro area 
financial stability 

The rise of artificial intelligence: benefits and risks for financial 
stability 

Private markets, public risk? Financial stability implications of 
alternative funding sources 

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Financial Stability Review, May 2024 – Contents 

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Foreword 

Financial stability conditions have improved since the last edition of the Financial 
Stability Review was published. The near-term risk of a deep recession accompanied 
by rising unemployment – a major source of concern six months ago – is much lower 
from today’s perspective, and disinflation has proceeded in parallel. 

At the same time, geopolitical tensions are a significant source of risk for not only euro 
area financial stability but also global financial stability. Policy uncertainty remains 
high around the world in a year featuring so many major elections. In such an 
environment, the scope for adverse economic and financial surprises is elevated, and 
the risk outlook for euro area financial stability remains fragile accordingly. 

Financial markets have been looking through these risks, with risk premia and volatility 
remaining unusually compressed by historical standards. Yet sentiment can change 
rapidly, not least given the geopolitical environment and pricing-for-perfection which 
creates the potential for large market reactions to disappointing news. 

While there are risks ahead, financial stability also depends on shock-absorbing 
capacity. So far, household and corporate balance sheets have proven resilient 
through this interest rate cycle, while euro area banks have withstood shocks well. 
This should not provide grounds for complacency, as pockets of vulnerability remain. 
Debt servicing capacities differ across corporates, with large real estate firms 
displaying greater vulnerability to rising interest rates. Lower-income households are 
finding it harder to service their debts, despite buoyant labour markets. At the same 
time, fiscal fundamentals remain vulnerable to negative growth surprises and fiscal 
slippage, as maturing debt is refinanced at higher interest rates. Parts of the non-bank 
financial intermediation sector, notably a cohort of open-ended investment funds, 
exhibit significant liquidity mismatches. At the same time, some non-bank entities may 
face risks related to relatively high leverage and portfolio concentration. 

This issue of the Financial Stability Review (FSR) includes three special features. The 
first examines the implications of geopolitical risk for euro area financial stability. The 
second analyses the risks and benefits associated with the rise of artificial intelligence, 
while the third focuses on the growing footprint of private markets. 

The FSR has been prepared with the involvement of the ESCB Financial Stability 
Committee, which assists the decision-making bodies of the ECB in the fulﬁlment of 
their tasks. The FSR promotes awareness of systemic risks among policymakers, the 
ﬁnancial industry and the public at large, with the ultimate goal of promoting financial 
stability. 

Luis de Guindos 
Vice-President of the European Central Bank 

Financial Stability Review, May 2024 – Foreword 

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Overview 

Financial Stability Review, May 2024 – Overview 

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Euro area financial stability vulnerabilities have eased, yet 
the outlook remains fragile 

Financial stability in the euro area has benefited from an improving economic 
outlook, but rising geopolitical risks could pose considerable downside risks. 
Favourable economic surprises in recent months have fostered investors’ baseline 
expectations that euro area inflation will reach the ECB’s target without a deep 
economic contraction, achieving a “soft-landing” scenario (Chart 1, panel a). 
Associated analyst expectations of interest rate cuts sparked a rally in financial 
markets, with growing signs of pricing-for-perfection creating the potential for outsized 
market reactions to disappointments. A key feature of post-pandemic balance sheet 
adjustment has been a fall in the debt ratios of euro area households, firms and 
sovereigns, which should bolster resilience in the medium to long term; however, 
some households, firms and sovereigns still have balance sheet vulnerabilities and 
could be challenged by rising debt service costs going forward. Euro area banks 
recorded strong profits in 2023 which, through the retention of earnings, helped to 
maintain resilience, but there are indications that the peak may have been reached. At 
the same time, the ongoing downturn in property markets, especially in commercial 
real estate, could have knock-on effects on the asset quality of some banks. Overall, 
despite reduced near-term recession risks and baseline expectations for an imminent 
return of moderate growth, risks to financial stability remain high. The likelihood of tail 
events materialising appears elevated as geopolitical risk has been on the rise 
(Chart 1, panel b). Should tensions ratchet up further, this could affect the supply of 
energy commodities, undermine confidence in the real economy, fuel inflation and 
spark risk aversion in financial markets (Special Feature A). Similarly, global 
economic policy uncertainty remains high, as countries with more than half of the 
world’s population are sending their citizens to the polls in 2024. 

Against this backdrop, three key themes are shaping the outlook for euro area 
financial stability. First, benign risk pricing in financial markets and structural liquidity 
vulnerabilities in non-banks harbour the potential for sudden shifts in market sentiment 
in response to adverse shocks, triggered, for example, by negative macro-financial 
surprises or heightened geopolitical tensions. Second, rising debt service costs are 
challenging euro area households, firms and sovereigns with weak balance sheets, 
and the downturn in property markets is, in some cases, compounding household and 
corporate vulnerabilities. Third, euro area banks have remained resilient, supported by 
strong profitability. Bank earnings appear set to moderate somewhat from recent 
highs in the next two years. At the same time, bank market values, while having risen 
somewhat, remain stubbornly below book values − indicating deeper seeded investor 
concerns about the durability of bank profitability. 

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Chart 1 
Positive macro surprises point to a soft landing, but tail risks remain elevated in the 
light of high macro-financial and geopolitical uncertainty 

a) Citi Economic and Inflation Surprise Indices 
for the euro area and the United States 

b) Global policy uncertainty and geopolitical 
risk index 

(May 2023-Apr. 2024, indices) 

(Jan. 2004-Apr. 2024, indices) 

Sources: Bloomberg Finance L.P., Caldara and Iacoviello*, Baker, Bloom and Davis** and ECB calculations. 
Notes: Panel b: the dashed lines represent the long-term averages over the period from January 1997 to April 2024. The global policy 
uncertainty index is shown until February 2024. 
*) Caldara, D. and Iacoviello, M., “Measuring Geopolitical Risk”, American Economic Review, Vol. 112, No 4, April 2022, pp. 1194-1225. 
**) Baker, S., Bloom, N. and Davis, S., “Measuring Economic Policy Uncertainty”, The Quarterly Journal of Economics, Vol. 131, No 4, 
November 2016, pp. 1593-1636. 

Asset prices remain vulnerable to adverse dynamics that 
may be amplified by liquidity risks in non-banks 

Expectations of monetary policy easing have boosted investor demand for 
risky assets, but risk sentiment in markets has been fickle. Expectations that 
monetary policy will ease around the world have been fuelling investors’ appetite for 
risky assets since October 2023, as markets have been pricing-in a soft landing for the 
global and euro area economies. Reflecting this, stock prices have increased and 
credit spreads have narrowed, with a short-lived reversal more recently (Chart 2, 
panel a). At the same time, equity market volatility has remained relatively subdued, 
despite the recent uptick and continued substantial uncertainty in both the 
macro-financial and geopolitical environments, and has diverged from volatility in 
interest rate markets, which has been elevated (Box 2). In this environment of 
substantial risks to growth and structurally higher funding costs, markets might 
underestimate and under-price the likelihood and the impact of adverse scenarios, 
which could cause vulnerabilities to build up. Moreover, there is a greater likelihood of 
negative surprises resulting in abrupt shifts in sentiment. Volatility in financial markets 
could increase significantly, should inflation deviate substantially from consensus 
expectations, if economic growth weakens or if geopolitical conflicts escalate further 
(Chart 2, panel b). Heightened concentration and high valuations in equity markets, 
notably in the United States, indicate scope for greater volatility and potential for a 

Financial Stability Review, May 2024 – Overview 

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market correction. Given deeply integrated global equity markets, financial stability 
risks for the euro area might stem from adverse spillovers from the United States. 

Chart 2 
Geopolitical tensions may spark volatility and trigger adjustments in financial markets, 
which could be amplified by non-banks with low liquidity and high leverage 

a) Global equity markets and 
high-yield corporate bond 
spreads 

b) Historical volatility 
distributions, by geopolitical 
risk regime 

c) Liquidity mismatch and 
leverage among euro area 
investment funds 

(1 Jan. 2021-7 May 2024; index, basis 
points) 

(3 Jan. 2000-7 May 2024, indices) 

(Q4 2023, ratios, bubble size: total assets, 
€ trillions) 

Sources: Bloomberg Finance L.P., Caldara and Iacoviello, ECB (IVF) and ECB calculations. 
Notes: Panel a: the MSCI All Country World Index is used for global equity markets; the ICE BofA Global High Yield Index is used for 
global high-yield bond spreads. Panel b: VIX – index for implied volatility in the US equity market, MOVE – index for implied volatility in 
the US Treasury bond market. Geopolitical risk is measured by the geopolitical risk index (GPRI) created by Caldara and Iacoviello, op. 
cit. High geopolitical risk denotes episodes when the GPRI was at least 2 standard deviations above its average since 2000. Boxplots 
show the distributions of standardised volatility measures since 2000, where whiskers denote the 5th and 95th percentiles. Panel c: 
includes open-ended investment funds only. Liquidity mismatch is defined as the ratio of investment fund shares issued to liquid assets 
(deposits and debt securities with a maturity of less than one year, euro area sovereign bonds, investment and money market fund 
shares, and advanced economy listed shares). Financial leverage is defined as total assets divided by shares issued. 

The non-bank financial intermediation sector could still amplify any market 
correction, given liquidity vulnerabilities, leveraged exposures and rising 
concentration risks. Non-banks have benefited from improving market conditions in 
recent months, supporting their portfolio valuations, while higher interest rates have 
also boosted investment income from debt securities. However, asset quality in 
non-bank portfolios may still be impaired by worsening corporate sector fundamentals 
and real estate market conditions together with rising geopolitical risk (Special 
Feature A). In this context, any shocks to market valuations could trigger a rise in 
investment fund outflows or margin calls on derivative exposures. Given low liquid 
asset holdings and significant liquidity mismatches in some types of open-ended 
investment funds, this could result in forced asset sales that may negatively affect 
wider financial stability (Chart 2, panel c). Although generally limited, pockets of 
elevated financial and synthetic leverage in some entities may add to spillover risks. In 
addition, concentration in equity portfolios − notably in investment funds due to 
exposures to US-based technology firms − has increased markedly in recent years 
(Chapter 4), making investment portfolios more vulnerable to idiosyncratic shocks or 
adverse developments in the US economy. For the insurance sector, uncertainties 
around a weak macro-financial outlook highlight possible profitability headwinds. 

Financial Stability Review, May 2024 – Overview 

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These include both underwriting profitability challenges for life insurers and 
consistently low returns on debt securities portfolios. 

Tight financial conditions are testing the resilience of 
vulnerable households, firms and sovereigns 

Euro area households, firms and sovereigns have so far remained resilient on 
aggregate, albeit with some pockets of vulnerability. The indebtedness of euro 
area households, firms and sovereigns has declined from post-pandemic highs 
(Chart 3, panel a), alleviating debt sustainability concerns. However, associated 
vulnerabilities remain elevated, especially among sovereigns. Here indebtedness 
remains above pre-pandemic levels, owing partly to a transfer of risk from the private 
sector to sovereign balance sheets during the pandemic as well as during the recent 
energy crisis and period of high inflation. The debt service costs of non-financial 
sectors are likely to remain at current high levels or even creep up further as the debt 
originally contracted at historically low interest rates and at long maturities continues 
to reprice at prevailing, significantly higher, interest rates. This means that a 
vulnerable cohort of highly indebted households, firms and sovereigns may still see 
their debt servicing capabilities challenged going forward. 

Sovereign financing conditions have improved, but fiscal fundamentals remain 
vulnerable to negative growth surprises and fiscal slippage. Sovereign borrowing 
costs have benefited from easier financing conditions of late and positive rating 
actions in some countries (Chart 3, panel b). Interest costs are set to rise further, 
however, especially for sovereigns with high short-term refinancing needs, as 
maturing public debt is rolled over at higher interest rates. Despite falling debt-to-GDP 
ratios in recent years, fiscal fundamentals remain fragile in a number of countries, as 
indicated by missed deficit targets in some cases in 2023. Given structural headwinds 
to potential growth from factors such as weak productivity, persistently elevated debt 
levels and budget deficits would be more likely to reignite debt sustainability concerns 
and push sovereign credit risk premia higher in the event of adverse macro-financial 
surprises. Risks of fiscal slippage in the light of a busy electoral agenda in 2024-25 (at 
both national and EU levels) or uncertainties around the exact implementation of the 
new EU fiscal framework could lead market participants to reprice sovereign risk. On 
the other hand, greater fiscal reform to ensure that public finances have a more 
growth-friendly composition could enhance the medium-term economic growth 
potential of the euro area, thereby mitigating debt sustainability risks. 

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Chart 3 
Debt levels in the non-financial sectors have fallen from pandemic highs, but debt 
service costs may still rise further 

a) Household, NFC and 
sovereign indebtedness 

b) Ten-year government bond 
yields and credit ratings of 
euro area sovereigns 

c) Lending rates to the euro 
area non-financial private 
sector 

(percentages of GDP) 

(percentages, rating buckets) 

(Jan. 2015-Mar. 2024, percentages) 

Sources: Bloomberg Finance L.P., LSEG, S&P Global Market Intelligence, Moody’s Analytics, Fitch Ratings, Eurostat and ECB (QSA), 
ECB (MIR) and ECB calculations. 
Notes: Panel a: NFCs stands for non-financial corporations. NFC debt is illustrated in unconsolidated terms, i.e. including intra-sectoral 
loans. “Pre-pandemic” indicates figures as at Q4 2019, “Pandemic peak” refers to Q1 2021, and the latest observation captures Q4 2023. 
Panel b: ratings and rating outlooks are aggregated from S&P, Moody’s and Fitch and are shown as at 31 October 2023 and 30 April 
2024. Rating outlooks are only indicated for those sovereigns for which the aggregated outlook has changed since October 2023. 
Aggregated outlooks can be determined by the outlook from a single agency; for instance, two stable outlooks and one negative outlook, 
which was the case for Italy in October 2023, are aggregated to form an overall negative outlook. 

Euro area household and corporate balance sheets have been bolstered by a 
resilient labour market and strong post-pandemic profits. Corporate profitability 
has continued to hold up relatively well, supporting firms’ debt servicing capacity 
(Section 1.3). Declining energy and other input costs have boosted corporate 
earnings despite weak consumer demand, although the impact of anaemic growth and 
higher labour costs on profit margins might not have fully materialised yet. While 
corporate insolvencies have continued rising to above pre-pandemic levels in a 
number of euro area countries, defaults and non-performing loan rates have remained 
relatively low. At the same time, euro area household vulnerabilities have been 
mitigated by the resilience of labour markets, coupled with government support 
measures and excess savings accumulated during the pandemic. While household 
and corporate debt-to-GDP levels have dropped below pre-pandemic readings, the 
pass-through of higher interest rates to debt service costs is incomplete. Continued 
loan repricing at higher market rates than on outstanding loans (Chart 3, panel c), 
together with weaker than expected growth and deteriorating labour market 
conditions, could erode household and corporate debt servicing capacity. At the same 
time, evaporating liquidity buffers (Chart 4, panel a) may render households and firms 
vulnerable to unexpected adverse shocks. 

Pockets of vulnerability remain, as high interest rates weigh on the debt 
servicing capacity of vulnerable households and firms. High debt service costs 
could prove especially challenging for firms with lower credit ratings, as reflected by 

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the rise in expected default frequencies in the high-yield segment. Expected default 
rates are also highly uneven across economic sectors, with firms operating in 
wholesale trade or in real estate seeing some of the largest increases in expected 
default rates (Chart 4, panel b). Defaults could rise if yields remain high, energy prices 
soar again or global supply chain disruptions intensify. Euro area households, 
especially those with lower incomes and in countries with mainly floating-rate 
mortgage lending, are being relatively more challenged by higher interest rates 
(Chart 4, panel c). However, middle-income households may be affected too, 
especially if labour market conditions were to weaken considerably. In such a scenario 
the implications for banks mortgage portfolios could become notable. 

Chart 4 
Declining liquidity buffers of euro area households and firms in recent years may 
weigh on the debt servicing capabilities of vulnerable cohorts 

a) Cash and deposit holdings 
of euro area households and 
NFCs 

b) One-year default rate 
forecasts in Europe, by 
industry 

c) Household expectations of 
payment difficulties in the 
next three months, by income 

(Q1 2016-Q4 2023, percentages of GDP) 

(June 2022, Mar. 2024, percentages) 

(Q1 2021-Q1 2024, percentages of 
consumers) 

Sources: Eurostat and ECB (QSA), ECB (CES), Moody’s Analytics and ECB calculations. 
Notes: Panel b: June 2022 is the month before the start of the recent monetary policy hiking cycle. Panel c: the share of consumers is 
calculated using survey weights, and the total number of surveyed households includes those who report not having a loan or answering 
“don’t know”. The sample of countries comprises Belgium, Germany, Spain, France, Italy and the Netherlands, and from April 2022 also 
includes Ireland, Greece, Austria, Portugal and Finland. The share of lower-income households is calculated as the average of the first 
and second income quintiles, middle-income households correspond to the third income quintile, and higher-income households 
comprise the average of the fourth and fifth income quintiles. The total shares are equal-weighted averages of the shares for mortgages 
and other loans. 

Tight financial conditions have underscored vulnerabilities in real estate 
markets, compounding the challenges faced by some households and firms. 
The sharp downturn in the commercial real estate (CRE) sector has continued 
(Chart 5, panel a), with subdued market activity continuing to hamper price discovery. 
Prices could decline further, given structurally lower demand for some CRE assets 
post-pandemic, notably in the office segment (Section 1.5). Sharp drops in rental 
income and profit margins since early 2022 have made real estate firms particularly 
vulnerable to losses, compounding the challenges posed by refinancing debt at higher 
rates (Box 1). The ongoing adjustment in residential real estate (RRE) markets has 
remained orderly, as households’ financial positions have been underpinned by the 

Financial Stability Review, May 2024 – Overview 

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strength of the labour market. There have also been signs of incipient stabilisation of 
euro area house prices at the aggregate level, but risks remain tilted to the downside, 
especially in countries with elevated debt levels and overvalued property markets. 
That said, the expected decline in borrowing costs might alleviate affordability 
challenges and boost loan demand going forward. Overall, the downturn in the RRE 
market should remain orderly, unless labour market conditions deteriorate 
significantly. 

Banks remained resilient, but face headwinds from weaker 
asset quality, lower revenues and cost of funding 

There are signs of deterioration in the asset quality of euro area banks, notably 
in CRE portfolios. While banks’ non-performing loan ratios remained at historically 
low levels just above 2% in 2023, there have been nascent signs of rising losses on a 
subset of loan portfolios that are more sensitive to cyclical downturns. In fact, CRE 
loan books have been the main driver of asset quality deterioration, reflecting both the 
downturn in euro area CRE markets and spillovers from the ongoing correction in US 
CRE markets to euro area banks with material exposures. That said, these portfolios 
are generally modest in size and should not have a systemic impact on the banking 
sector. For some banks with above-average CRE exposure, though, a marked 
deterioration in CRE asset quality could pose challenges. At the same time, the credit 
risk outlook for household and corporate portfolios remains tilted to the downside, as 
macro-financial conditions are weak and borrowers are increasingly feeling the impact 
of higher interest rates. As a result, banks may face the risk of higher provisioning 
costs if risks in the non-financial sectors materialise, not least because collateral 
values may not to be fully reflected in banks’ balance sheets. 

Euro area banks continue to face funding cost headwinds. Since the previous 
issue of the Financial Stability Review was published, bank bond yields have declined 
and new business deposit rates have lost upward momentum in line with market 
expectations of looming policy rate cuts (Chart 5, panel b). However, the average cost 
of outstanding bank funding has risen further, reflecting a shift in composition towards 
more expensive sources of funding. In particular, depositors seeking higher 
remuneration have been shifting from overnight deposits to higher-yielding term 
deposits. At the same time, bond funding has also been growing as it replaces other 
sources such as the ECB’s targeted longer-term refinancing operations (TLTROs). 
Looking ahead, bank funding costs seem set to remain high as maturing liabilities 
reprice at higher levels and the composition of funding continues moving back towards 
long-run averages featuring a higher share of term deposits and bonds. Overall 
funding costs might therefore still increase further, even if policy rates start to decline. 

Low bank valuations indicate market concerns regarding the longer-term 
sustainability of bank profits. In recent years, strong euro area bank profitability has 
primarily been driven by rising net interest margins. This is because bank funding 
costs adjusted more slowly than lending rates due to the automatic repricing of 
floating-rate loans. As such, floating-rate assets could now turn into a headwind for 
banks’ interest income as policy rates are expected to fall, while overall funding costs 

Financial Stability Review, May 2024 – Overview 

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may increase still further. Indeed, the recent decrease in interest rate spreads 
suggests that euro area banks are likely to see their net interest margins decline 
(Chart 5, panel c). Margin compression, together with continued muted lending 
volumes, could serve to reduce banks’ operating income and compound the 
challenges stemming from deteriorating asset quality, ultimately weighing on bank 
profitability. These profitability uncertainties are also visible in euro area bank 
price-to-book valuations, which have continued to hover around 0.7 (Chapter 3), well 
below those of some major international peers. 

Chart 5 
Euro area bank profitability has likely peaked, with signs of worsening asset quality 
and higher funding costs posing headwinds to euro area banks going forward 

a) CRE values, RRE prices and 
net NPL inflows across euro 
area countries 

b) Bank funding costs on new 
funding, by type of funding 
source 

c) Euro area banks’ net 
interest rate spread and 
margin 

(Q4 2023, annual percentage changes) 

(Jan. 2016-Mar. 2024, percentages) 

(Jan. 2016-Mar. 2024; percentage points, 
percentages) 

Sources: Bloomberg Finance L.P., Dealogic, Eurostat and ECB (RESR), ECB (MIR, RESC, supervisory data) and ECB calculations. 
Notes: Panel a: NPL stands for non-performing loan. Panel b: market implied €STR is shown for April 2024 until March 2026. Panel c: net 
interest margin is shown until the fourth quarter of 2023. 

From a structural perspective, a greater need to respond to cyber and climate 
risks, and strong interlinkages with the non-bank financial intermediation 
(NBFI) sector, may also challenge euro area banks. Next to the headwinds 
associated with challenging macro-financial conditions that lie ahead, euro area banks 
need to press ahead with digital transformation, not least so that they can respond to 
the growing threat of cyber risks as well as address the opportunities and challenges 
associated with the rise of artificial intelligence (Special Feature B). Euro area banks 
also need to carefully manage the implications of the transition to a greener economy. 
In addition, elevated vulnerabilities in the NBFI sector may produce spillover risks for 
euro area banks, given strong interconnections between these sub-sectors of the 
financial system, not least via the funding channel (Box 4). 

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Macroprudential policies can help safeguard and 
strengthen resilience across the financial system 

All in all, financial stability vulnerabilities have eased, but the outlook remains 
fragile. Financial stability conditions have improved somewhat since the previous 
issue of the Financial Stability Review was published. This includes some positive 
economic surprises and faster than expected disinflation, underpinning expectations 
in financial markets of a soft landing. That said, despite improved baseline 
expectations, the likelihood of tail events appears elevated. In particular, the 
materialisation of downside risks to economic growth, more persistent inflation 
outturns or acute geopolitical stress could expose existing vulnerabilities. This would 
notably concern risks associated with the potential for disorderly adjustments in 
financial markets, coupled with debt servicing challenges for highly indebted 
households, firms and sovereigns and their adverse knock-on effects on the asset 
quality of euro area banks. 

Preserving the resilience of the banking sector and, where conditions are 
favourable, further increasing macroprudential space remain crucial in an 
uncertain macro-financial environment. The resilience of the euro area banking 
sector is, on aggregate, underpinned by strong capital and liquidity positions. 
Standard regulatory metrics point towards strong liquidity resilience overall, despite 
more than 90% of borrowed TLTRO funds being repaid over recent quarters. On 
aggregate, solvency ratios remain robust, supported by organic growth from high bank 
profitability. In recent years, euro area macroprudential authorities have also 
implemented a comprehensive set of measures that have bolstered banks’ resilience 
and enhanced the availability of releasable capital buffers. As such, it is prudent to 
maintain macroprudential capital buffers to ensure that they remain available in case 
of headwinds. Prevailing borrower-based measures can continue to act as structural 
backstops to ensure sound lending standards in a framework where capital-based and 
borrower-based measures complement each other. The recent strength of profitability 
of the banking sector can be used to further increase macroprudential space through 
releasable capital buffers, to further strengthen the resilience of bank lending to the 
economy in the event of marked economic downturns. 

Structural vulnerabilities in the NBFI sector require a comprehensive policy 
response to enhance its resilience from a macroprudential perspective. A large 
market footprint and the interconnectedness of non-bank financial institutions call for a 
comprehensive set of policy measures to increase the sector’s resilience. This 
includes policies aimed at enhancing the liquidity preparedness of non-bank market 
participants to meet margin and collateral calls (Box 5), tackling risks from non-bank 
leverage (Box 6), mitigating liquidity mismatch in open-ended funds and enhancing 
the resilience of money market funds to liquidity shocks (Section 5.2). A more 
integrated EU-wide system of supervision for non-banks would also build a level 
playing field and reduce the potential for regulatory arbitrage. A resilient NBFI sector 
would also help to foster more integrated capital markets, which could enhance 
financial stability and complement the objectives of the capital markets union. 

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1 

Macro-financial and credit environment 

1.1 

While risks of a deep recession have declined, geopolitical 
risks are on the rise 

Investor sentiment has been recovering alongside an improving 
macro-financial outlook, although prospects for growth vary across euro area 
countries. Headline inflation in the euro area is now projected to fall to 2.3% in 2024, 
compared with 2.7% expected just six months ago. In parallel, although economic 
growth in 2024 is likely to be weaker than previously hoped, there is less likelihood of 
the euro area experiencing a severe downturn. Taken together, this has improved 

Financial Stability Review, May 2024 – Macro-financial and credit environment 

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near-term investor sentiment. Looking ahead, the financial stability outlook will 
increasingly depend on mixed medium-term growth prospects. On the one hand, 
economic activity is expected to pick up more strongly over the period 2025-26 (Chart 
1.1, panel a), supported by resilient labour markets and a recovery in households’ real 
incomes. On the other hand, structural challenges (related to, for example, slow 
digitalisation, weak innovation and an ageing population) remain a drag on 
productivity and income growth. Finally, current growth expectations vary 
considerably across the euro area (Chart 1.1, panel b), making some countries more 
vulnerable to future adverse shocks than others. 

Chart 1.1 
The near-term economic outlook is improving unevenly across countries, while 
medium-term growth challenges remain 

a) Economic growth outlook in the euro area  b) Distribution of real GDP growth forecasts 

across euro area countries for 2024 and 2025 

(2018-26; index, 2018 = 100) 

(Apr. 2024, percentages) 

Sources: ECB staff macroeconomic projections for the euro area, March 2024, Consensus Economics Inc. and ECB calculations. 
Notes: Panel a: alternative post-2019 GDP paths use different assumptions about annual GDP growth rates. Panel b: the cross-country 
distributions of GDP growth forecasts are based on average country forecasts made by professional forecasters in April 2024 for 
Belgium, Germany, Ireland, Greece, Spain, France, Italy, the Netherlands, Austria, Portugal and Finland. 

Risks to the macro-financial outlook remain elevated. Several such risks are 
related to external factors. Global demand could surprise to the downside if tight 
financing conditions continue to squeeze incomes and expenditure more strongly than 
expected, or if higher than expected inflation in the United States leads to a delayed 
easing of US monetary policy spilling over to tighter financing conditions globally. 
Divergent policy paths between the United States and the euro area would in turn 
increase the risk of adverse spillovers to European financial markets (Chart 1.2, 
panel a). Demand for euro area exports could be further weakened if the ongoing 
adjustment in property markets in China has a more pronounced, negative impact on 
its broader economy. As some euro area economies with relatively weaker near-term 
growth prospects depend heavily on exports to China, this would further amplify 
divergence between growth outcomes in the euro area. While progress has been 
made in bringing euro area inflation down, domestic price pressures are still high, 
owing in part to strong wage growth which could still surprise to the upside given how 

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tight labour markets are. Globally diverging monetary policy paths could also lead to 
higher inflation via their impact on the euro exchange rate and import prices.1  Finally, 
geopolitical tensions could, as a result of their impact on commodity prices and global 
supply chains, lead to renewed inflationary pressures in the euro area as well. 

Chart 1.2 
Elevated external risks cloud the macroeconomic outlook for the euro area 

a) Evolution of economic 
growth forecasts for 2024 

b) Container shipping costs 
and global supply chain 
pressures 

c) New trade restrictions 
around the world, by year of 
introduction 

(Jan. 2023-Apr. 2024, percentages) 

(Jan. 2018-Apr. 2024; index, USD) 

(2014-May 2024, number of measures) 

Sources: Consensus Economics Inc., Bloomberg Finance L.P., Federal Reserve Bank of New York (AMEC), Global Trade Alert and ECB 
calculations. 
Notes: Panel a: average GDP growth forecasts among professional forecasters. Panel b: higher values for the Global Supply Chain 
Pressure Index represent greater pressures on supply chains. Panel c: all measures introduced globally that restrict cross-border flows 
of goods, services and foreign direct investment. Data for 2024 are as of 7 May 2024. 

Geopolitical tensions have risen, posing risks to the global growth outlook and 
the euro area disinflation process. Russia’s war against Ukraine and the conflict in 
the Middle East are key sources of tail risk. The recent attacks on cargo ships on the 
Red Sea trade route triggered an abrupt rise in shipping costs between Asia and 
Europe in December 2023 (Chart 1.2, panel b) and global supply chain pressures 
have been on the rise since last autumn. The immediate risks to inflation and growth in 
the euro area from the Red Sea attacks seem limited owing to their minimal impact on 
oil production costs, current spare capacity in global shipping and subdued global 
demand. However, the impact on euro area growth and inflation could be substantial if 
the disruptions were to escalate to the broader region and last longer. The recent 
intensification of the Iran-Israel conflict has increased the probability of such a tail-risk 
scenario materialising. The expected reduction in oil production by its main exporters, 
as well as supply disruptions to oil and gas facilities in Russia and Ukraine, pose 
further upside risks to oil and gas prices. The rise in geopolitical tensions between 
major economies in recent years is also leading to weakening global trade links. For 
example, the share of imports to the United States from China declined from 25% in 

1    A material strengthening of the US dollar could also pose a challenge for emerging markets, with 

potential adverse spillovers to economic activity in the euro area. 

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2017 to 15% in 2023, and the number of protectionist measures targeting cross-border 
trade is increasing globally (Chart 1.2, panel c). Continued geopolitical tensions pose 
the risk of economic and financial fragmentation in the world economy, with potential 
adverse effects on financial stability in the euro area and globally. These potential 
effects could include slower productivity growth and higher production costs resulting 
from less efficient resource allocation, greater macro-financial volatility due to reduced 
international risk-sharing opportunities, and lower profitability and a higher cost of 
funding for financial institutions on the back of reduced cross-border capital flows. In 
this context, the record number of elections due to take place across the world in 2024 
are likely to keep the uncertainty around global economic policies elevated. 

1.2 

Lax fiscal policies may reinforce public debt sustainability 
concerns 

While sovereign financing conditions have improved, borrowing needs are high 
and could be tested by rising geopolitical tensions and other risks. Euro area 
sovereigns have benefited from easier global financing conditions in recent months, 
and demand for sovereign debt has been strong as investors try to lock in higher yields 
before the expected cuts in central bank interest rates materialise (Chart 1.3, panel a). 
Spreads between lower- and higher-rated sovereigns have also declined (Chart 3, 
panel b in the Overview), reflecting favourable risk sentiment, as well as better 
prospects for growth in lower-rated countries and declining debt-to-GDP ratios. 
Nevertheless, since yields on new sovereign issuances are still above average yields 
on outstanding debt, sovereign interest burdens are continuing to rise. This could lead 
to greater challenges ahead, particularly for countries with greater short-term 
financing needs. Any reassessment of sovereign risk by market participants due to 
high debt levels and lenient fiscal policies could raise borrowing costs further and have 
negative financial stability effects, including via spillovers to private borrowers and to 
sovereign bond holders. Finally, rising geopolitical tensions and upcoming elections in 
many countries are increasing uncertainty around future borrowing needs. 

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Chart 1.3 
Sovereign debt issuance is currently benefiting from strong investor demand, but 
projected large financing needs leave sovereigns vulnerable to adverse shocks 

a) Cumulative sovereign debt issuance in the 
euro area, by maturity at origination 

b) Past and projected structural primary 
balances across euro area countries 

(Jan. 2020-Mar. 2024; € billions, years) 

(2016-19 and projections for 2024-25, percentages of GDP) 

Sources: Eurostat and ECB (GFS), European Commission (AMECO) and ECB calculations. 
Notes: Panel a: the bars in the chart show cumulative debt issuance since the start of the calendar year. Panel b: for Greece (not shown), 
the average structural primary balance was 8.7% of GDP in the period 2016-19 and is expected to average 1.9% of GDP in the period 
2024-25. 

National budget deficits are expected to stay larger than they were before the 
pandemic as many of the support measures taken have remained in place. 
While most of the energy and inflation support measures introduced after the Russian 
invasion of Ukraine are being phased out, many of the measures taken during the 
pandemic have not been fully rolled back. Moreover, structural primary balances (i.e. 
budget balances adjusted for the impact of changes in economic growth due to 
business cycle fluctuations and excluding interest payments on outstanding debt) are 
expected to remain well below pre-pandemic levels over 2024-25. This is the case for 
almost all euro area countries, irrespective of their starting level of sovereign debt 
(Chart 1.3, panel b). Potential fiscal slippages are an additional concern, as 
weakening economic activity has already contributed to some countries missing deficit 
targets in 2023, and the upcoming cycle of elections is increasing the risk of fiscal 
targets being missed as well. The lack of envisaged fiscal consolidation, combined 
with high debt levels, makes national budgets vulnerable to intensifying geopolitical 
tensions should these require increases in spending on defence, for example. It would 
also be more difficult to accommodate additional investment in areas such as climate 
change and digital technology, which would have a negative effect on euro area 
growth potential. 

Financial Stability Review, May 2024 – Macro-financial and credit environment 

18 

 
 
 
 
Chart 1.4 
Despite falling somewhat in recent years, projected sovereign debt levels remain high 

a) Change in euro area government 
debt-to-GDP and its drivers 

b) Projected government debt-to-GDP ratios 
across euro area countries   

(2021-25, percentages of GDP and percentage point contributions)  (2019 and 2025, percentages of GDP) 

Sources: European Commission (AMECO), Eurostat and ECB (GFS) and ECB calculations. 
Note: Panel a: values for 2024 and 2025 are projections. 

High levels of debt make euro area sovereigns vulnerable to adverse shocks, 
especially given the structural weakness in productivity and potential growth. 
While the government debt-to-GDP ratio in the euro area has fallen gradually from its 
pandemic-era peaks, the drop has been primarily driven by the post-pandemic 
recovery in nominal GDP, which has more than offset the impact of higher debt service 
costs on debt levels (Chart 1.4, panel a). With weaker nominal growth prospects 
ahead and little change expected in the structural primary balances, the debt-to-GDP 
ratio is falling at a slower pace. As a result, public debt levels in most euro area 
countries are expected to remain above pre-pandemic levels in the short to medium 
term (Chart 1.4, panel b). More importantly, structural headwinds to potential growth, 
from weak productivity for instance, are raising concerns about longer-term debt 
sustainability, making sovereign finances more vulnerable to adverse shocks and 
elevating risks to the financial stability outlook. 

1.3 

Euro area firms are coping with rising debt service costs 

Resilient post-pandemic profitability has helped firms to service the rising cost 
of debt, but weak growth and high labour costs are creating challenges. The 
interest payments faced by non-financial corporations (NFCs) have risen further in 
recent quarters (Chart 1.5, panel a) and are expected to remain close to their current 
levels or even increase for some corporates in the near future, even if the cost of new 
borrowing continues to decline. This is because a large share of firms still need to 
refinance loans and bonds that were originated at low interest rates, before the recent 
surge in borrowing costs. For example, at the end of 2021, around 25% of firms’ bank 
loans had interest rates fixed for between two and five years. Firms’ debt repayment 

Financial Stability Review, May 2024 – Macro-financial and credit environment 

19 

 
 
 
 
capacity has held up relatively well so far, supported by the strong revenue growth 
seen in recent years (Box 1). At the same time, however, firms’ profitability is 
weakening and is expected to decline further in 2024, owing to the poor outlook for 
growth for 2024 (Chart 1.5, panel b) and the fact that labour costs are still growing 
strongly. Since access to external funding could remain constrained by tight bank 
lending standards for a longer period of time (Chapter 3), a significant and protracted 
slowdown in earnings growth would make debt repayments much more difficult to 
meet, especially for firms that have already drawn on their cash buffers. 

Chart 1.5 
If profitability weakens, firms’ ability to accommodate rising debt service costs could be 
challenged, especially in sectors most sensitive to changes in interest rates 

a) Interest payments and net 
entrepreneurial income 
growth 

b) Expected growth in the 
nominal earnings of listed 
euro area companies 

c) Median interest coverage 
ratio and cash buffers in 
selected sectors 

(Q1 2005-Q4 2023; percentages, 
year-on-year percentage point changes) 

(2 June 2023-26 Apr. 2024, year-on year 
percentage point changes) 

(Q4 2019 vs Q4 2023, percentages) 

Sources: Eurostat and ECB (MNA, QSA), LSEG, S&P Global Market Intelligence and ECB calculations. 
Notes: Panel a: the debt service ratio is the sum of the interest paid in the current and the past three quarters divided by the sum of net 
operating surplus and property income in the current and the past three quarters for the NFC sector. Net entrepreneurial income is the 
sum of gross operating surplus and property income net of depreciation. Panel b: analysts’ forecasts for nominal earnings growth for 
2024 and 2025 are calculated for the companies included in the MSCI EMU index. Panel c: the cash-to-assets ratio is defined as cash 
plus cash equivalents over total assets. ICR stands for interest coverage ratio and is defined as the ratio of earnings before interest, 
taxes, depreciation and amortisation (EBITDA) to interest expense. Firm-level ICR and the cash-to-assets ratio are computed as 
four-quarter moving averages. “Comm. services” stands for communication services; “Consumer discr.” stands for consumer 
discretionary goods. 

Vulnerabilities are elevated, particularly in those sectors and countries most 
exposed to the impact of higher interest rates. While the overall debt servicing 
capacity of euro area firms has been resilient, tight financing conditions have had a 
bigger impact on some countries and sectors than on others. Among large firms, the 
ability to meet interest payments from earnings has declined substantially since the 
end of 2019 in those sectors, such as real estate and discretionary consumer goods, 
affected by weaker demand on the back of higher interest rates on consumer and 
mortgage loans (Chart 1.5, panel c). Firms in the real estate sector have seen 
particularly large declines in their profitability since mid-2022, making them highly 
vulnerable to continuing tight financing conditions and to downside risks to the growth 
outlook (Section 1.5). Default rates on bank loans to commercial real estate firms are 
rising (albeit from low levels), reflecting eroding financial health. The same also 

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applies to loans to small and medium-sized enterprises, since they have smaller 
liquidity buffers and lower profit margins than bigger firms (Chapter 3). Finally, 
corporate interest burdens have also increased more strongly in euro area countries 
where floating-rate lending is prevalent than in countries with a larger share of 
fixed-rate loans (Box 1). At the same time, if downside risks do not materialise, NFCs 
with floating-rate loans will also benefit more quickly from the expected declines in 
market rates than borrowers with fixed-rate loans. 

Chart 1.6 
Subdued borrowing is contributing to declining indebtedness of euro area corporates 

a) NFC financing flows and demand for bank 
loans 

b) Change in corporate indebtedness since Q2 
2022, by country 

(Q1 2018-Q1 2024; € billions, index) 

(Q2 2022 vs Q4 2023, percentages) 

Sources: ECB (BLS, BSI, CSEC), Eurostat and ECB (QSA) and ECB calculations. 
Notes: Panel a: the “bank loan demand” indicator reflects changes anticipated by banks. It is equal to the difference between the sum of 
the shares of banks responding that demand for corporate loans is expected to “increase considerably” and “increase somewhat” and the 
sum of the shares of banks responding that demand for corporate loans is expected to “decrease somewhat” and “decrease 
considerably”. Panel b: the chart shows the ratio of the gross non-consolidated debt (i.e. including intra-sectoral loans) of NFCs to GDP. 
Changes in the gross NFC debt-to-GDP ratio are calculated for the period Q2 2022-Q4 2023. The chart does not show Luxembourg, 
where the gross NFC debt-to-GDP ratio increased from 315.5% in Q2 2022 to 316.8% in Q4 2023. The non-consolidated NFC debt 
levels for Cyprus include the debt held by special-purpose entities. 

Lending standards are expected to remain tight for some time, which could 
create additional headwinds for firms with high near-term refinancing needs. 
New borrowing by firms has remained subdued across all borrowing instruments in 
recent months (Chart 1.6, panel a), particularly for small and newly established firms. 
To a certain extent, this weakness reflects low demand for external financing because 
of high borrowing costs and an uncertain business outlook, as well as tight credit 
standards imposed by lenders. While the cost of new credit has been falling recently 
as lenders start to price-in the expected decline in central bank interest rates, it 
remains historically high, with the average interest rate on new bank loans to 
corporates at above 5% since September 2023. With the outlook for near-term growth 
subdued and lending standards expected to remain tight going forward, the near-term 
outlook for corporate borrowing is weak. This could pose a risk to firms’ debt rollover 
capacity, especially if growth continues to surprise to the downside and if the 

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21 

 
 
 
 
downward pressure on corporate profitability reduces firms’ capacity to substitute 
external with internal funding. 

The ongoing corporate deleveraging should support firms’ access to external 
financing once the economy picks up and financing conditions ease. Weak new 
borrowing since late 2022 and the negative effect of past high inflation on corporate 
debt ratios have contributed to considerable deleveraging among firms, with the 
aggregate NFC gross-debt-to-GDP ratio in the euro area declining from 106.4% in the 
second quarter of 2022 to 98.4% in the fourth quarter of 2023. Although the countries 
with the highest levels of NFC debt have seen the largest declines in indebtedness 
(Chart 1.6, panel b), corporate debt levels are still elevated in some jurisdictions. At 
the same time, the decline in overall indebtedness, as long as it remains orderly, will 
likely put firms in a better position to access external funding in the medium term, once 
interest rates start declining and economic activity gains strength. 

Box 1 
Corporate debt service and rollover risks in an environment of higher interest rates 

Prepared by Lucyna Górnicka, Maciej Grodzicki, Thore Kockerols and Chloe Larkou 

The rapid increase in interest rates could weaken the ability of firms to service and roll over 
their debt and, consequently, worsen the outlook for bank asset quality. Since the pandemic, 
several factors have helped to keep euro area corporate sector profitability remarkably resilient to 
shocks. First, firms managed on aggregate to improve their revenues as economic activity rebounded 
after the pandemic. Second, pent-up demand made it easier for them to pass rising energy and input 
costs (affected by supply bottlenecks and Russia’s war against Ukraine) through to consumers. After 
the ECB started raising its policy rates in the middle of 2022, however, firms started facing higher 
costs to service their debts, initially on floating-rate debt and later also on their fixed-rate debt. This 
box combines firm-level balance sheet data with loan-level data to assess the joint impact of resilient 
post-pandemic profitability and higher financing costs on the debt servicing capacity of euro area 
firms. As a measure of debt servicing capacity, the box uses an adjusted interest coverage ratio 
(ICR).2  As the financial data of non-listed euro area firms are typically released with a long lag, firms’ 
earnings in 2023 are estimated using sector and country aggregate earnings growth rates. Interest 
payments are estimated based on actual lending rates available at the individual loan level. 

The estimated interest burdens of euro area firms may be signalling a mild increase in either 
loan defaults or restructurings, or both. Most firms are expected to continue servicing their debts 
without difficulty, despite higher interest rates. This can be attributed to low starting levels of interest 
payable, high cash buffers that were bolstered during the pandemic or a sizeable increase in earnings 
since 2021. The share of loans to firms assessed to be unable to meet their interest payments with 
earnings and accumulated cash – meaning they have an ICR below 1 – is estimated to have risen 

2    We define the interest coverage ratio as earnings before interest, depreciation and amortisation 

(EBITDA) plus cash and cash equivalents, divided by annual interest payments. This indicator measures 
the ability of firms to meet interest payments in the next 12 months and does not capture firms’ 
vulnerability over a longer horizon. The ICR decreases when a firm’s capacity to service its debt 
weakens. The ICR is correlated with other measures of a firm’s financial distress; see the box entitled 
“Corporate vulnerabilities and the risks of lower growth and higher rates”, Financial Stability Review, 
ECB, November 2023. Firms that cannot service their debt may adjust by reducing investment outlays or 
personnel costs, or selling assets, meaning that an ICR below 1 does not necessarily lead to them 
defaulting on their debt. 

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from about 7.9% to 8.4% since 2021 (Chart A, panel a).3  A further 8.1% of loans have been granted 
to firms which could face challenges in making principal repayments, as they have small earnings 
buffers above their contractual interest payments (ICRs of between 1 and 2.5). Since this renders 
firms vulnerable to revenue or input cost shocks, some of them may need their debt to be reprofiled to 
remain solvent. 

Chart A 
Corporate interest burdens have increased more in sectors and countries most exposed to the effects 
of higher interest rates 

a) Distribution of loans to 
non-financial firms with interest 
coverage ratios below 10 

b) Change in the share of loans to firms projected to fail to meet interest 
payments from earnings and cash balances 

(percentages) 

(end-2023 vs end-2021, percentage points) 

Sources: ECB (AnaCredit), Bloomberg Finance L.P., Eurostat, BvD Electronic Publishing GmbH – a Moody’s Analytics company and ECB calculations. 
Notes: The interest coverage ratio (ICR) is defined as earnings before interest, tax, depreciation and amortisation plus cash and equivalents, divided by annual 
interest payments. The latest available data on earnings refer to 2021; projections for 2023 are obtained by indexing earnings at the NACE-2 sector level in line 
with sectoral turnover aggregates reported by Eurostat. Annual interest payments are estimated from loan-level data, taking into account the increase in interest 
rates due to indexation to a floating-rate index. Where a figure for depreciation and amortisation is not available, it is assumed to be zero. Data cover about 
461,000 firms active in 2019 and 2021 which had loans outstanding at the end of 2023. Panel a: the distribution of the ICR has been censored at 10. Panel b: the 
heatmap shows changes in the share of total outstanding firm loans with an ICR<1, broken down by economic sector and country. Economic activity 
classification in accordance with NACE Rev.1. Sector L refers to real estate activities, sectors D+E refer to Electricity, Gas, Water, sector F refers to Construction, 
sector H refers to Transporting and Storage, sector C refers to Manufacturing, sectors M+N refer to Professional activities, sector G refers to Wholesale and 
Retail Trade, sector I refers to Accommodation and Food, sector J refers to Information and Communication. Countries sorted by increasing share of fixed-rate 
loans. Grey areas indicate country-economic activity pairs for which data on fewer than 70 firms are available. Some euro area countries are not presented due 
to limited availability of corporate financial data. 

The impact of higher debt service costs has been disproportionately strong in the real estate 
sector and in countries where loans are mostly contracted with floating interest rates. The 
larger increase in the interest payable of real estate firms compared with other sectors reflects the 
larger negative impact of weaker demand (amid higher mortgage interest rates) on their net revenues 
(Chart A, panel b). Interest burdens have also increased more strongly in several smaller euro area 
countries where floating-rate lending is prevalent, contrasting with milder increases in fixed-rate 
countries such as Germany and France. 

3    The high number of firms with an ICR below 0 already pre-pandemic is consistent with other studies that 

find a comparable share of illiquid firms (i.e. those not able to cover financial expenses with cash flows 
and cash) based on the Orbis database. See, for example, Kalemli-Ozcan, S., Gourinchas, P.-E., 
Penciakova, V. and Sander, N., “COVID-19 and SME Failures”, IMF Working Papers, International 
Monetary Fund, 2020. Illiquid firms might still continue operating thanks to access to credit and debt 
restructuring, for instance. 

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Chart B 
Pressure on refinancing corporate loans is expected to ease in the coming years, but banks have 
been slow to recognise the impact of higher debt service costs on loan quality 

a) Distribution of loans to non-financial firms, by 
interest coverage with earnings and cash balances 
and by next loan refinancing date 

b) Share of outstanding loans within ICR buckets, by 
forbearance, default and Stage 2 status 

(percentages) 

(percentages) 

Sources: ECB (AnaCredit), Bloomberg Finance L.P., Eurostat, BvD Electronic Publishing GmbH – a Moody’s Analytics company and ECB calculations. 
Notes: See Notes to Chart A. Panel b: “Forbearance” refers to refinanced loans or loans with modified terms and conditions. “Default” refers to loans that are 
deemed unlikely to pay or that are more than 90/180 days past due. “Stage 2” refers to loans for which credit risk has increased significantly since initial 
recognition, but which are not impaired. The status categories are not mutually exclusive, meaning that shares of outstanding loans by status are not additive. 

Some vulnerable firms may benefit from refinancing in a more favourable environment, if 
market rates fall as expected. Even if vulnerable firms manage to continue servicing their loans, a 
low interest coverage ratio raises refinancing risk because banks need to re-assess the 
creditworthiness of the borrower before agreeing to the terms of the new loan. The cohorts of firms 
which are due to refinance their loans after 2024 are less vulnerable than those which have secured 
financing for shorter terms (Chart B, panel a), as they are expected to benefit from gradually falling 
interest rates. 

Banks should recognise credit distress promptly and offer viable solutions to firms which 
struggle to service their debt. Lower interest coverage ratios are usually associated with higher 
shares of defaulted and underperforming (Stage 2) loans. However, even among firms with low 
interest coverage ratios, more than half of the bank loans have not been restructured and remain 
performing (Chart B, panel b). Weak interest coverage is likely to lead to trade-offs for banks between 
offering forbearance solutions and enforcing the loans, where the latter would likely lead to more 
abrupt credit loss. It is important that such forbearance solutions are viable for the customer and that 
their financial implications are accurately recognised in bank financial statements. Otherwise, 
unsustainable forbearance may lead to higher credit losses in the long run. 

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1.4 

Strong labour markets support household resilience 

Euro area households continue to benefit from record employment levels and 
rising real wages and incomes, with further real wage growth expected ahead. 
Employment growth remained positive in late 2023, despite some signs of an 
impending turn in labour markets several months previously (Chart 1.7, panel a). 
Purchasing Managers’ Indices (PMIs) for employment, which are early indicators of 
future labour market conditions, have been climbing out of negative territory (values 
below 50) over the past few months. The continued strength of labour markets can be 
observed across the board, with only a few countries seeing unemployment rates rise. 
At the same time, real wage growth picked up enough to turn positive in the third 
quarter of 2023, pushing up household income. After several difficult years, growth in 
compensation per employee is expected to outpace inflation in 2024 and beyond amid 
rapid disinflation (Chart 1.7, panel b), which will considerably bolster the financial 
situation of households. 

Chart 1.7 
Labour markets remain robust, while positive real wage and income growth bolsters 
households’ financial situations 

a) Employment growth and PMI indicators for 
employment 

b) Growth in compensation per employee 

(Jan. 2022-Mar. 2024; left-hand scale: indices, right-hand scale: 
quarter-on-quarter percentage changes) 

(2022-26E, annual percentage growth rates) 

Sources: Eurostat and ECB (MNA), S&P Global Market Intelligence, ECB staff macroeconomic projections for the euro area, March 2024 
and ECB calculations. 
Notes: Panel a: the latest observation for employment growth is for Q4 2023. Panel b: shaded bars are forecasted values from the March 
2024 ECB staff macroeconomic projections. 

The cost of new borrowing and outstanding debt service have plateaued, while 
real income growth is supporting households’ debt servicing capabilities. 
Interest rates on new and renegotiated mortgages as well as on new consumer loans 
peaked in the fourth quarter of 2023, likely in anticipation of policy rate cuts later in 
2024 (Chart 1.8, panel a). Countries with predominantly variable-rate mortgages have 
seen their debt service costs increase considerably. At the same time, households’ 
debt servicing capabilities in countries with mainly fixed-rate mortgages will depend on 

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future interest rates when mortgage fixation periods end. The less rapid rise in interest 
rates together with the recent pick-up in wages across the euro area led to the 
aggregate debt service-to-income ratio plateauing as of the fourth quarter of 2023. 
Additionally, households have likely used excess savings accrued during the 
COVID-19 pandemic to reduce debt burdens in recent years (Overview, Chart 4, 
panel a), limiting the overall deterioration in their ability to service their debts 
compared with the previous hiking cycle between 2006 and 2008. 

Chart 1.8 
Households’ cost of new borrowing has plateaued, and aggregate debt service seems 
to be at a turning point, as expectations of future debt servicing capabilities worsen 

a) Euro area household debt service ratio and 
cost of new borrowing 

b) Expectations of difficulties making 
mortgage payments in the next three months, 
by income quintile 

(Q1 2003-Q1 2024, percentages) 

(Jan. 2022-Jan. 2024, percentage of consumers) 

Sources: Eurostat and ECB (QSA), ECB (MIR, CES) and ECB calculations. 
Notes: Panel a: the latest observation for the household debt service ratio is for Q4 2023. The debt service ratio is defined as the ratio of 
fixed debt service costs (i.e. interest payments plus amortisations) to disposable income. Fixed debt service costs assume identical 
repayment of principal over the average maturity of the debt and an average interest rate. Disposable income is expressed as a function 
of income, the average interest rate and the average remaining maturity of the debt stock. Panel b: the percentage of consumers is 
calculated using survey weights. The total number of households surveyed includes those who report not having a loan or not knowing 
how to answer. The sample of countries comprises Belgium, Germany, Spain, France, Italy and the Netherlands, and from April 2022 
also includes Ireland, Greece, Austria, Portugal and Finland. 

Risks to household financial stability appear manageable at present, yet the 
share of vulnerable households is rising, especially in lower-income brackets. 
The combination of persistently strong labour markets, expected high wage growth, 
healthy savings cushions at pre-pandemic levels and the high share of fixed-rate 
mortgages in the euro area is ensuring that severe risks to the household sector’s 
financial situation remain contained.4  However, the share of households expecting to 
face difficulties in making mortgage payments in the next three months jumped in 
January 2024 compared with 2023 (Chart 1.8, panel b). This increase is especially 
pronounced for both lower- and, unusually, middle-income households. Additionally, 
microsimulations of household survey data suggest that the share of households with 

4    The impact of elevated debt burdens may also be cushioned by government support programmes which 

are currently under discussion in some euro area countries. 

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a dangerously high debt service-to-income ratio in countries with mainly variable-rate 
mortgages increased to around 15% as of the fourth quarter of 2023 from a stable 
level of around 12% in 2021 and early 2022.5  While debt held by lower-income 
households makes up only around 11.4% of total household debt in the euro area, the 
sharp increase in expected difficulties reported by households in the middle income 
quintile, which accounts for 14.7% of total household debt, could be indicative of a 
larger financial stability issue in the future, especially if interest rates do not fall as 
expected in 2024, real wage growth turns out to be much lower than expected and the 
labour market weakens notably. 

1.5 

Correction under way in property markets, notably the 
commercial segment 

Mortgage demand is expected to pick up in the second quarter of 2024, but new 
lending remains subdued. The steep increase in borrowing costs since the start of 
the present rate-hiking cycle has, together with subdued consumer confidence and 
housing market prospects, been the main driver behind the falling demand for 
mortgages. The decline in demand for new housing loans eased in 2023 and is 
expected to reverse entirely in the second quarter of this year (Chart 1.9, panel a). If 
this reversal materialises, it would be the first time in two years that banks have 
reported net positive demand for mortgages. Expectations that a lower cost of 
mortgage debt would boost the affordability and attractiveness of housing appear to 
be the key factor behind this change in outlook. Borrowing costs already declined 
slightly for four consecutive months between November 2023 and March 2024, 
bringing the average interest rate from 4.01% to 3.77%. However, the volume of new 
loans for house purchase remains subdued in 2024 and stands below the lows of 2023 
(Chart 1.9, panel b). 

5    The threshold for a dangerously high debt service level is defined here as a total debt 

service-to-gross-income ratio of above 30%. This is a conservative measure far above the common ratio 
of 30% debt service in relation to net income and is associated with a significantly increased risk of 
default. 

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27 

 
 
 
Chart 1.9 
Banks expect demand for housing loans to increase on the back of lower borrowing 
costs, but new loan origination remains subdued for the moment 

a) Changes in demand for mortgage loans in 
the euro area 

b) New loans to households for house 
purchase, excluding renegotiations 

(Q1 2020-Q2 2024, net balances of survey responses) 

(Jan. 2019-Mar. 2024, € billions) 

Sources: ECB (BLS, MIR) and ECB calculations. 

There are some signs of stabilisation in residential real estate (RRE) prices, but 
downside risks remain. Euro area RRE prices declined 1.1% year on year in the 
fourth quarter of 2023. This fall in aggregate euro area RRE prices masks significant 
differences across countries, with around two-thirds of euro area countries still 
exhibiting positive price dynamics in the same period. In addition, high-frequency data 
on RRE prices available for a selected number of countries indicate that the drop in 
RRE prices in some countries might have slowed or even come to a halt in the second 
half of last year (Chart 1.10, panel a). The orderly contraction in RRE prices has led to 
a reduction in overvaluation measures, which is reflected in slightly lower tail risk for 
euro area RRE prices compared with the third quarter of 2022 (Chart 1.10, panel b). 
Nonetheless, downside risks remain elevated in some euro area countries, as housing 
affordability is at low levels owing to high interest rates and high prices, with some 
markets still showing signs of overvaluation. The tightening in financial conditions has 
been followed by a stark deceleration in RRE investment, which will likely have a 
negative impact on supply going forward (Chart 1.10, panel c). The reduction in 
housing supply and expectations of rising construction prices, albeit much slower than 
in the recent past, might to some extent mitigate the risk of prices falling substantially 
going forward. 

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Chart 1.10 
The orderly contraction in RRE prices has reduced tail risks to RRE prices, but 
significant downside risks are likely to persist in some countries 

a) RRE price dynamics in 
selected countries 

b) One-year forward predicted 
tail risk in euro area RRE 
prices 

c) Survey indicators on 
residential construction and 
residential investment growth 

(Dec. 2019-Mar. 2024; index: Dec. 2019 = 
100) 

(Q1 2016-Q2 2024, percentages) 

(Jan. 1999-Mar. 2024; left-hand scale: net 
percentages and percentages, right-hand 
scale: index) 

Sources: ECB, Europace, Immobiliare.it (Italy), Confidencial Imobiliário (Portugal, sourced from BIS), Arco Real Estate (Latvia), Národná 
banka Slovenska, Statistics Finland, Indominio.es (Spain), Central Statistics Office (Ireland), Statistics Netherlands, S&P Global Market 
Intelligence and ECB calculations. 
Notes: Panel a: the chart includes monthly data up to December 2023, February 2024 or March 2024 for the following countries: 
Germany, Ireland, Spain, Italy, Latvia, the Netherlands, Portugal and Finland. The data for Slovakia are quarterly and up to December 
2023. An average listing price index is used for Italy, while a hedonic price index based on transaction prices is used for all the other 
countries. Data for Latvia reflect prices of apartments in Riga and thus only a portion of the country’s real estate market. The data for 
Portugal capture around 40% of the real estate market, as transactions that do not go through estate agents are excluded. As a result, 
official country statistics might differ from the data provided here, as they capture the entire market at the cost of lower frequency. Panel 
b: the chart shows the results from an RRE price-at-risk model based on a panel quantile regression on a sample of 19 euro area 
countries. The chart shows the 5th percentile of the predicted RRE price growth for the euro area aggregate and the 10th-90th percentile 
range of this estimate across individual euro area countries. Further details on the methodology can be found in the article entitled “The 
analytical toolkit for the assessment of residential real estate vulnerabilities”, Macroprudential Bulletin, Issue 19, ECB, October 2022. 

The outlook for offices and lower-quality commercial real estate (CRE) 
continues to deteriorate, which is having a negative effect on the resilience of 
real estate firms. Transaction activity in CRE markets remains subdued, with almost 
half as many transactions completing in the last two quarters of 2023 as in the 
equivalent period in 2022. Furthermore, market intelligence indicates little to no 
pick-up in activity over the start of 2024. While this low level of market activity is 
inhibiting price discovery, there is already evidence of a significant price correction 
occurring in markets, with prices down 8.7% annually as of the fourth quarter of 2023 
(Overview). The outlook for the office market is particularly bleak. Increased use of 
work-from-home options has created a structural drop in demand for this asset, which 
is reflected in a significant decline in rent growth expectations compared with 
pre-pandemic dynamics. Lower-quality assets are the most affected, and expectations 
in this segment continue to deteriorate due to additional concerns about energy 
efficiency requirements and capital expenditure costs. However, conditions in euro 
area markets do appear more benign than in the United States, attributable to more 
extensive working from home in the United States combined with an excess of supply 
going into the downturn (Chart 1.11, panel a). Falling rental income, rising capital 

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expenditures and higher financing costs pose a triple threat to real estate firms. The 
largest real estate firms in the euro area have seen their profit margins contract 
sharply since the start of 2022, which has left around half of them in loss-making 
territory (Chart 1.11, panel b). 

Chart 1.11 
The outlook for CRE markets continues to deteriorate, with real estate firms facing 
increasing profitability pressure 

a) 12-month rent growth expectations for the 
office market 

b) Share of firms with negative net profit in the 
real estate sector and median net profit 
margin 

(Q4 2023, percentages) 

(Q1 2017-Q3 2023, percentages) 

Sources: RICS, S&P Global Market Intelligence and ECB calculations. 

The downturn in RRE markets has remained orderly thus far, while some signs 
of materialising risk can be observed in CRE markets. The downward adjustment 
in RRE prices remains orderly, with signs of stabilisation in some countries. Generally, 
the contraction in RRE prices has been larger in countries where properties showed 
signs of greater overvaluation at the start of the rate hike cycle. Risks remain tilted to 
the downside, however, especially in those countries where debt levels are elevated 
and properties might still be overvalued. The commercial segment has seen a steeper 
downturn, and rising financing costs pose challenges to the debt servicing capacity of 
real estate firms, especially where rental income is also under pressure. This 
development is reflected in positive and rising non-performing loan inflows in banks’ 
CRE portfolios, although these remain contained for now. Banks’ aggregate 
exposures are substantially smaller to CRE than to RRE and are unlikely to be large 
enough at the euro area level to threaten the solvency of the banking system as a 
whole. However, these exposures are not evenly spread across the banking system, 
and stress could arise among the euro area’s most exposed banks (Chapter 3). 
Additionally, an adverse outcome of such a scenario could be amplified by procyclical 
selling among non-banks, particularly real estate investment funds (Chapter 4). 

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30 

 
 
 
 
2 

Financial markets 

2.1 

Markets adjust to expected shift in monetary policy 

Expectations of global monetary policy easing have been boosting investor 
demand for risky assets. The disinflation trend, partly supported by moderating 
energy prices, has led to investor expectations that major central banks will start to 
ease monetary policy in 2024. Market participants are currently pricing-in around 115 
basis points of policy rate cuts over the next 12 months in the euro area and 95 basis 
points in the United States (Chart 2.1, panel a). While longer-dated risk-free rates 
rebounded from the strong decline observed close to the end of 2023, the expected 

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shift in monetary policy still supported risky asset valuations. Increased risk appetite 
contributed to the strong outperformance of the riskiest asset classes (Chart 2.1, 
panel b). While some positive economic surprises in the first months of 2024 have led 
investors to postpone their expectations surrounding the timing of a first policy rate 
cut, investors remain confident that inflation in advanced economies might reach its 
2% target without a deep economic contraction (a “soft landing”). 

Chart 2.1 
Shift in monetary policy prospects has boosted investor confidence and risk appetite 

a) Expected policy rate changes over the next 
12 months 

b) Global asset class performance since the 
previous issue of the Financial Stability 
Review 

(Jan. 2021-May 2024, basis points) 

(22 Nov. 2023-7 May 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: the latest observations are for 7 May 2024. The chart shows the difference between 1Y1M forward overnight index swap 
(OIS) rates and current overnight rates (euro area – €STR, United States – SOFR). The equity market bottom and all-time high indicated 
are based on the daily-close values for the EURO STOXX Index. Panel b: HY stands for high yield; IG stands for investment grade. 
Performance is based on the following indices: crypto-assets – Bloomberg Galaxy Crypto Index; private equity – FTSE Private Equity 
Buyout Index (for United States); equities – MSCI ACWI Index; bonds – ICE BofA indices; commodities – Bloomberg Commodity Index 
Total Return. 

Positive real risk-free rates might mitigate some financial stability concerns but 
might also challenge the most vulnerable corporates. Investor expectations 
suggest that while policy rates will go down, they will remain well above the zero lower 
bound. Consequently, long-term real risk-free rates are expected to remain in positive 
territory – at around 0.25% for the euro area – also in steady state (Chart 2.2, panel a). 
While the era of negative interest rates in the decade before the inflation outbreak was 
associated with the rise of a number of financial stability risks, the new regime may 
bring long-term benefits for the stability of the financial system.6  Nevertheless, the 
ongoing period of transition could still expose some vulnerabilities and increase 
market volatility. For example, the stress seen in the banking sector in March 2023 
showed that some individual financial entities are particularly vulnerable to interest 
rate risk. Since then, market participants have priced in tail risks as skewed to the 

6    See, for example, “Macroprudential policy issues arising from low interest rates and structural changes in 
the EU financial system”, ESRB, November 2016, and Hermans, L., Kostka, T. and Vassallo, D., “Asset 
allocation and risk taking under different interest rate regimes”, Working Paper Series, No 2803, ECB, 
March 2023. 

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32 

 
 
 
 
 
downside, as reflected in the prices of options on short-term sovereign bonds (Chart 
2.2, panel b). 

Chart 2.2 
Market participants expect long-term real rates to stay higher for longer, but risks for 
short-term rates are perceived as skewed to the downside 

a) Five-year real risk-free rates five years 
ahead 

b) Skewness in implied volatility arising from 
options on short-term sovereign bonds 

(Jan. 2021-May 2024, percentages) 

(Jan. 2021-May 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: The latest observations are for 7 May 2024. Panel a: difference between 5Y5Y forward OIS rates (euro area – €STR, United 
States – SOFR) and 5Y5Y inflation swap forward rates (euro area – HICP ex tobacco, United States – CPI). Panel b: difference between 
implied volatility in 5% delta put and 5% delta call one-month options on 2Y sovereign bond futures (euro area – Euro Schatz listed on 
Eurex, United States – US Treasury Note listed on CBOT). 

The structure of the corporate bond market has delayed the full impact of 
higher interest rates on businesses. One way corporates can hedge against the 
impact of unexpected interest rate changes on their funding costs is to issue fixed-rate 
bonds instead of floating-rate bonds. In this case funding costs mostly increase when 
the debt has to be rolled over in a higher-rate environment. Given that fixed-rate bonds 
are dominant in corporate bond structures in both the euro area and the United States 
(Chart 2.3, panel a), the aggregated impact of past policy tightening has been 
smoothed over time.7  In addition, in the euro area lower-rated corporate borrowers 
issued a record amount of debt shortly before the onset of the recent tightening cycle, 
which has also kept the share of bonds maturing in the near term at low levels (Chart 
2.3, panel b). This enabled lower-rated borrowers to reduce issuance in 2022 and 
2023, which shielded them from the immediate effects of higher risk-free rates and 
wider spreads on their funding costs. However, increased rollover needs going 
forward might accelerate the impact of higher rates. Furthermore, the recently 
observed shift towards shorter debt maturities is leaving lower-rated firms more 
exposed to future market conditions. 

7    Moreover, non-financial corporations in the euro area are net fixed-rate payers in interest rate derivatives, 

which suggests that part of the floating rate debt outstanding might also be hedged. 

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Chart 2.3 
High share of fixed-rate corporate bonds and a supportive maturity structure has so far 
slowed the impact of policy tightening on the most vulnerable issuers 

a) Share of fixed-rate corporate bonds by 
jurisdiction and rating 

b) Share of bonds with less than three years to 
maturity in benchmark euro area corporate 
bond indices 

(7 May 2024, percentages) 

(Jan. 2014-May 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: IG stands for investment grade; HY stands for high yield, NR stands for not rated. Calculated for bonds issued in local 
currency. Investment grade means at least one investment grade rating from Fitch, Moody’s or S&P. Panel b: the latest observations are 
for 7 May 2024. “Investment grade” refers to bonds included in the ICE BofA Euro Corporate Index, while “high yield” refers to bonds 
included in the ICE BofA Euro High Yield Index. 

Total bond funding costs are still expected to increase further. At the end of 
2021, marginal bond funding costs were substantially lower than total bond funding 
costs in both the euro area and the United States (Chart 2.4, panel a), indicating that 
pandemic-related policy easing had not yet been fully transmitted. The rapid increase 
in bond yields over 2022 has reversed these dynamics but, until recently, the overall 
increase in total bond funding costs had been relatively limited. While current bond 
yields reflect the policy rate cuts anticipated by investors, the limited scale of the 
expected easing cycle leaves scope for further total funding cost increases (proxied by 
the distance to the 45-degree line in the chart). This might put pressure on more 
indebted corporates, especially if the subdued economic growth currently observed in 
the euro area continues. In the sovereign bond space, while total funding costs are 
also expected to increase further, the scale of expected increase varies substantially 
across individual countries (Chart 2.4, panel b). In contrast to the situation for 
corporates, it appears that more of the past tightening has already been transmitted to 
more indebted sovereign issuers than to less indebted ones (the higher the marginal 
cost of bond funding, the closer it is to the total cost of bond funding). This is because 
of the significant amount of lower-rated sovereign debt which has already been rolled 
over at higher rates. In addition, the recent substantial compression of spreads has 
further mitigated the expected additional increase in average sovereign funding costs. 

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34 

 
 
 
 
Chart 2.4 
Bond funding costs will increase further as issuers refinance their debt 

a) Total versus marginal corporate bond 
funding costs by jurisdiction 

b) Total versus marginal euro area sovereign 
bond funding costs by country 

(Dec. 2021-May 2024, percentages) 

(Dec. 2021-May 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: The latest observations are for 7 May 2024. Total funding cost is proxied by the average yield at issue on outstanding fixed-rate 
bonds weighted by the amount outstanding. When data on yield at issue were not available the coupon rate was used instead. The 
marginal funding costs are proxied by the average yield-to-worst on outstanding fixed-rate bonds weighted by the amount outstanding. 
Panel a: calculated for bonds included in ICE BofA indices: Euro Corporate Index, Euro High Yield Index, US Corporate Index, US High 
Yield Index. Panel b: calculated for bonds included in the ICE BofA All Maturity All Euro Government Index. 

2.2 

Benign pricing of risk keeps asset prices vulnerable to 
shocks 

Low risk perceptions might mask underlying vulnerabilities and lead to 
excessive risk-taking. Since the publication of the previous edition of the Financial 
Stability Review in November 2023, implied volatility indices for risky asset classes 
have remained subdued both in historical terms and in comparison with the implied 
volatility in the interest rate markets (Chart 2.5, panel a). Given the role played by 
diversified equity indices in reflecting broad macroeconomic conditions, volatility 
indicators based on them (such as VIX and VSTOXX) are perceived as benchmark 
market-based risk indicators. While low implied volatility in financial markets can 
support financial stability to the extent that it properly reflects sound fundamentals and 
a stable risk outlook, it might also reflect some underestimation of financial stability 
vulnerabilities by market participants (Box 2). In addition, because financial 
institutions commonly use implied volatility indices in their risk management, 
prolonged periods of subdued volatility might incentivise excessive risk-taking.8  This 

8    See, for example, Brunnermeier, M. and Sannikov, Y., “A Macroeconomic Model with a Financial Sector”, 

The American Economic Review, Vol. 104, No 2, February 2014, pp. 379-421. 

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35 

 
 
 
 
 
could, in turn, lead to a substantial compression of risk premia (Chart 2.5, panel b) 
and add to non-linear dynamics during shocks.9 

Chart 2.5 
Most implied volatility indices remain subdued and might incentivise risk-taking 

a) Implied volatility indices against the 
distribution for the last ten years 

b) Risk premia versus implied volatility 
indices for euro area risky assets 

(8 May 2014-7 May 2024, percentiles) 

(May 2014-Apr. 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: IG stands for investment grade; HY stands for high yield. Based on the following indices for the euro area and the United 
States respectively: interest rate – SMOVE, MOVE; equity – VSTOXX, VIX; IG credit – Itraxx/Cboe Europe Main 1M Volatility Index, 
CDX/Cboe IG 1M Volatility Index; HY credit: Itraxx/Cboe Europe Crossover 1M Volatility Index, CDX/Cboe HY 1M Volatility Index. Panel 
b: for high-yield corporate bonds “risk premia” is proxied by option-adjusted spreads for the ICE BofA Euro High Yield Index while for 
equities it is proxied by the 5Y CAPE yield over the 5Y real risk-free rate for EURO STOXX. 

The rally in equity markets has pushed both valuations and concentration 
levels higher. Robust earnings, investor optimism and the related compression of risk 
premia have resulted in a strong equity performance in recent months, taking major 
indices to all-time highs. In the United States, some equity valuation metrics have 
reached decade-high values (Chart 2.6, panel a), fuelling concerns of overvaluation 
or, even, an AI-related asset price bubble. Although cyclically adjusted metrics are still 
below dotcom bubble levels, they are also substantially above the historical median, 
suggesting that there is scope for a market correction and lower long-term returns 
going forward (Chart 2.6, panel b). In addition, there have been increasing concerns 
over heightened market concentration, as the largest companies in the United States 
now account for a historically high share of broad index capitalisation (Chart 2.6, 
panel c). This could lead to the prevalence of idiosyncratic risks related to the key 
themes driving earnings expectations higher – as was the case for internet 
development in the 1990s and is the case for AI currently. Elevated uncertainty 
surrounding the ultimate impact of AI on the real economy could therefore contribute 
to high volatility in the overall equity market, irrespective of whether the “AI rally” is 
displaying asset price bubble dynamics or not. In the euro area, while market 
concentration has also risen, equity valuation indicators have not increased to the 

9    See, for example, the box entitled “Volatility-targeting strategies and the market sell-off”, Financial 

Stability Review, ECB, May 2020. 

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36 

 
 
 
 
 
levels seen in the United States. As the respective equity markets are deeply 
integrated, financial stability risks for the euro area might relate mostly to spillovers 
from the United States or to potential negative earnings surprises, particularly if 
subdued economic growth continues. 

Chart 2.6 
Heightened US equity valuations indicate scope for a larger market correction, while 
extreme market concentration might indicate elevated idiosyncratic risks 

a) Equity market composite 
valuation metric relative to the 
ten-year average 

b) CAPE ratio and subsequent 
long-term realised returns in 
the US equity market 

c) Share of the top 1% of 
companies in broad equity 
index capitalisation 

(Jan. 2021-Apr. 2024, z-scores) 

(Jan. 1988-Apr. 2024; ratio, percentages) 

(Jan. 1995-May 2024, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: average z-scores of the following valuation metrics for EURO STOXX (euro area) and the S&P 500 (United States): 
price-to-book ratio, price-to-forward (12-month) earnings ratio, price-to-long-term (ten-year) inflation-adjusted earnings ratio, 
price/earnings-to-growth ratio (growth rate calculated as the average of annualised five-year historical earnings growth and annualised 
two-year blended-forward earnings growth) and inverse risk premia proxied by five-year CAPE yield less five-year real 
(inflation-swap-adjusted) government bond yield (German for the euro area). Panel b: CAPE stands for cyclically adjusted 
price-to-earnings, where earnings for the last ten years are adjusted by inflation and averaged. Calculations are for the S&P 500. 
“Dotcom bubble” refers to the period between December 1999 and March 2000. Panel c: the latest observations are for 7 May 2024, 
calculated for the EURO STOXX (euro area) and the S&P 500 (United States). 

While the corporate sector is perceived as resilient on aggregate, pockets of 
vulnerabilities have become more apparent. Buoyant investor sentiment has also 
been observed in the corporate bond market. Progress seen in the convergence of 
inflation towards central bank targets has strengthened baseline expectations among 
investors that the global economy will experience a soft landing. In such a scenario, 
default rates – even those for more indebted borrowers – are expected to remain 
contained, which has supported the continued compression of high-yield bond 
spreads in both the euro area (Chart 2.7, panel a) and the United States (Chart 2.7, 
panel b). While this would be a desirable outcome from a financial stability 
perspective, there are still some concerns over the heterogeneous situation of 
individual sectors. In the euro area, this has been reflected in the substantial increase 
in spread dispersion to levels last seen during the global financial crisis (Chart 2.7, 
panel c). The sectoral split indicates that distressed borrowers are concentrated in the 
real estate sector, which has recently become more vulnerable because of the 
downturn in the commercial segment (Chapter 1). While the small share of such 
troubled borrowers points to limited potential spillovers to the broader corporate bond 
market, it might reflect the deteriorating asset quality of some bank loan portfolios 

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(Chapter 3). By contrast, in the United States spreads have compressed substantially 
even for the lowest-rated borrowers, which might reflect a better economic outlook. 

Chart 2.7 
Corporate spread compression reflects optimism about borrowers’ resilience, but 
sectoral-specific risks seem to be on the rise 

a) Default rate forecast and 
spread for high-yield bonds in 
the euro area 

b) Default rate forecast and 
spread for high-yield bonds in 
the United States 

c) Dispersion of high-yield 
bond spreads in the euro area 
and the United States 

(Jan. 2020-Apr. 2024; left-hand scale: 
percentages, right-hand scale: basis points) 

(Jan. 2020-Apr. 2024; left-hand scale: 
percentages, right-hand scale: basis points) 

(Jan. 2008-May 2024, basis points) 

Sources: Bloomberg Finance L.P., Moody’s Analytics and ECB calculations. 
Notes: Panel a: option-adjusted spreads for the ICE BofA Euro High Yield Index and the 12-months-ahead baseline default rate forecast 
for European high-yield bonds by Moody’s. Panel b: option-adjusted spreads for the ICE BofA US High Yield Index and the 
12-months-ahead baseline default rate forecast for US high yield-bonds by Moody’s. Panel c: the latest observations are for 7 May 2024. 
The difference between the option-adjusted spreads for BB and CCC (or lower) bonds included in ICE BofA Bond Indices. 

Investor concerns about euro area sovereign debt sustainability have 
decreased greatly, despite medium-term vulnerabilities. Declining uncertainty in 
the interest rate market has continued to be one of the key drivers of sovereign spread 
compression in the recent period (Chart 2.8, panel a). In addition, substantial debt 
issuance by more vulnerable countries has been well absorbed by market 
participants, in part due to the growing demand for duration exposure. Investors have 
become more confident that risks in the sovereign bond market will remain contained. 
Consequently, the market pricing of sovereign credit risk still appears benign in 
comparison with the views of credit rating agencies (Chart 2.8, panel b). Because of 
the rise in interest expenses and still-elevated debt levels, some euro area countries 
may experience significant spread widening if they are unable to consolidate their 
fiscal positions. This may prove challenging, given the subdued economic growth 
outlook (Chapter 1). 

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Chart 2.8 
While sovereign spread compression is supported by the declining implied volatility of 
interest rates, investors might be overly optimistic in their assessment of risk 

a) Euro area sovereign spreads and implied 
interest rate volatility 

b) Euro area sovereign ratings versus 
market-implied ratings 

(Jan. 2021-May 2024; left-hand scale: basis points, right-hand 
scale: index) 

(7 May 2024; Moody’s rating, standardised rating scale) 

Sources: Bloomberg Finance L.P., Moody’s Analytics and ECB calculations. 
Notes: Panel a: the latest observations are for 7 May 2024. Spreads are against German bonds for bonds included in the ICE BofA All 
Maturity All Euro Government Index (excluding German bonds). Average is weighted by the amount outstanding. The size of the 
interquartile range shows the difference between the first and third quartiles of the distribution of spreads across bonds. Panel b: each 
data point shows an average of market-implied ratings from bond and credit default swap (CDS) pricing, based on Moody’s MIR 
methodology.* 
*) See Dwyer, D.W., Moore, D. and Wang, Y., “Moody’s Market Implied Ratings: Description and Methodology”, Moody’s Analytics. 

Box 2 
Low implied equity market volatility could underestimate financial stability vulnerabilities 

Prepared by Kasper Goosen, Magdalena Grothe, Peter McQuade, Andrzej Sowiński and Stefan Wredenborg 

Implied equity market volatility has been low in recent years, in both absolute and relative 
terms. Abstracting from short-lived spikes, implied equity market volatility has broadly declined since 
March 2020, despite tighter monetary policy, rising geopolitical tensions and a balance of risks to 
economic growth tilted to the downside. At the current juncture, low implied volatility in equity markets 
contrasts with signals from some leading economic indicators (Chart A, panel a) and still-elevated 
implied volatility in interest rate markets; the ratio of the two is at the lowest level in decades for both 
the United States and the euro area (Chart A, panel b). In addition, the subdued volatility skewness in 
the equity markets points to benign pricing of the downside risks (Chart A, panel c). This box 
discusses factors behind low levels of implied equity market volatility, its divergence from the implied 
volatility in interest rate markets and possible implications for financial stability, including 
underestimation of risks and related to this excessive risk-taking. 

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Chart A 
Implied equity market volatility seems subdued but, as in the past, it might rise quickly 

a) Historical distribution of implied 
volatility in equity markets in 
periods of expected economic 
growth or contraction proxied by 
leading economic indicators 

b) Implied volatility in equity 
markets relative to interest rate 
markets 

c) Implied volatility skewness in 
equity markets 

(Jan. 2000-Apr. 2024, percentage points) 

(Jan. 2000-Apr. 2024, ratio) 

(Jan. 2007-Apr. 2024, percentage points) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: based on the Conference Board Leading Economic Indicators, with positive year-onr-year change indicating growth. The whiskers correspond to 
the minimum and maximum of monthly average values of equity market implied volatility (euro area – VSTOXX, United States – VIX). Panel b: ratio of equity 
market implied volatility (VSTOXX – euro area, VIX – United States) to interest rate market implied volatility (euro area – SMOVE, United States – MOVE). Panel 
c: difference between implied volatility in 5% delta put and 5% delta call one-month options on the EURO STOXX 50 (euro area) and the S&P 500 (United 
States). 

Several factors may have contributed to the low levels of implied equity market volatility. 
During the period of relatively high inflation since 2021, diversified equity portfolios might have been 
seen as offering better inflation protection than fixed-coupon bonds, as nominal corporate earnings, 
from which equities pay a dividend, tend to grow with the price level. More recently, progress in 
bringing down inflation without a deep economic contraction has fostered investor optimism. This has 
been reflected in a sustained period of rising equity prices and declining realised volatility, which 
comoves strongly with implied volatility. While broader risks to the economic outlook prevail, lower 
implied equity market volatility may have also been supported by declining uncertainty regarding the 
growth outlook, visible, for example, in analyst expectations (Chart B, panel a). In addition, investors 
might expect that low correlations across stock returns could prevail and further contribute to low 
volatility at index level (Chart B, panel b).10  Subdued demand for tail-risk protection could be another 
potential explanatory factor. Investors might assume that major central banks now have more scope 
to ease monetary policy in response to financial stability risks than they did at the onset of the inflation 
surge. This may have led to expectations – which might not necessarily hold – that despite elevated 
tail risks, their materialisation would only lead to a transitory period of higher equity price volatility. 

10    When correlations across individual share prices are low, more diverse changes within the stock price 

index tend to cancel out and the overall index performance is more stable. 

Financial Stability Review, May 2024 – Financial markets 

40 

 
 
 
 
 
 
Chart B 
Progress towards a soft landing and low correlations across individual stocks supported VIX decline 

a) Standard deviation of real GDP 
growth expectations and implied 
volatility in the US equity market 

b) Implied broad market volatility 
and implied correlations between 
individual stocks in the US equity 
market 

c) Spread between implied and 
subsequent realised equity market 
volatility 

(Jan. 2015-Apr. 2024, percentage points) 

(2 Jan. 2017-7 May 2024, percentage points) 

(Jan. 2017-Apr. 2024, percentage points) 

Sources: Bloomberg Finance L.P., Consensus Economics Inc. and ECB calculations. 
Notes: “COVID-19 turmoil” refers to the pandemic-related market crash that occurred between 21 February and 16 March 2020; “Volmageddon” refers to the 
period from 1 to 5 February 2018, when stress in the US equity market was induced by forced unwinding of outsized short volatility positions.* Panel a: standard 
deviation of analysts’ one-year-ahead real GDP growth expectations. Panel b: “Implied correlation”, as measured by the Cboe Implied Correlation Index, 
captures the average expected correlation between the top 50 stocks in the S&P 500 index. Solid black fitted line is an exponential function. Panel c: spread 
between 30-day implied volatility (euro area – VSTOXX, United States – VIX) and subsequently realised 30-day volatility of underlying indices (euro area – 
EURO STOXX 50, United States – S&P 500). 
*) See Augustin, P., Cheng, I. and Van den Bergen, L., “Volmageddon and the Failure of Short Volatility Products”, Financial Analyst Journal, Vol. 77, No 3, 2021. 

Increasingly common short volatility strategies may also have suppressed implied equity 
market volatility and increased the risk of sudden repricing. These strategies aim to profit from 
declining or low equity volatility by selling equity options or taking short positions on VIX-based 
derivatives. Most of the time, they provide positive returns thanks to positive volatility risk premia – the 
difference between implied and subsequently realised volatility (Chart B, panel c) – but suffer large 
losses when there are spikes in volatility. Substantial profits from such strategies in recent years have 
increased interest in deploying them, thus potentially contributing to the downward trend in the VIX.11 
In addition, there has been growing interest in trading options on the day of their expiry (“0 days to 
expiry” or “0DTE”), potentially also among “short volatility” traders.12  In view of the increasingly 
crowded positions in such trades, their abrupt unwinding − triggered for example by a tail event − 
could lead to a disorderly correction and volatility feedback loops, as was the case during the 
“Volmageddon” volatility spike of February 2018 which led to large losses on short volatility strategies. 
The historically high end-of-day exposures to broad US equity market volatility instruments (Chart C, 

11    Investment funds that add a “short volatility” component to their broad market exposure, when pursuing a 
“covered call” strategy for instance, have experienced substantial inflows over the last two years. Their 
selling activity might put downward pressure on the prices of options used to calculate the VIX. See also 
Todorov, K. and Volkov, G., “What could explain the recent drop in VIX?”, BIS Quarterly Review, Bank for 
International Settlements, March 2024, pp. 6-7. 

12    While outsized supply of 0DTE options does not affect the VIX directly, it might have some dampening 

impact on its level if, for instance, market-makers decide to proxy-hedge their positions with longer-dated 
options or due to the deployment of specific term spread strategies. 

Financial Stability Review, May 2024 – Financial markets 

41 

 
 
 
 
 
 
panel a), as well as an intraday build-up of positions in 0DTE options, could make such market 
adjustments less orderly.13 

Chart C 
While positions in equity volatility instruments accumulate, high implied volatility in interest rate 
markets points to downside risks to GDP and equity prices 

a) Open interest in US broad equity 
market volatility instruments 

b) One-year ahead distribution of 
US and euro area GDP growth with 
and without conditioning on 
current high implied interest rate 
market volatility 

c) Response of US and euro area 
equity prices to a global risk-off 
shock 

(Jan. 2007-Apr. 2024, millions) 

(Apr. 2024, percentage change per annum) 

(1 Sep. 2005-26 Apr. 2024, percentage changes) 

Sources: Bloomberg Finance L.P., ECB, LSEG and ECB calculations. 
Notes: Panel a: open interest in S&P 500 options also includes options on the S&P 500 mini, S&P 500 nano and SPDR S&P 500 ETF, all adjusted to reflect the 
same notional. Open interest in VIX futures and options also includes mini VIX futures, adjusted to reflect the same notional. Panel b: predicted quantiles of 
year-on-year GDP growth distribution one year ahead as of April 2024, estimated with quantile regressions using a set of explanatory variables from January 
1989 (January 1999 for the euro area) to April 2024, with and without implied interest rate market volatility (United States – MOVE, euro area – SMOVE). For 
both the euro area and the US, the lower 10th percentile (not shown in the chart) is estimated to be lower when the MOVE/SMOVE is included. Panel c: the dots 
represent the mean estimate of the response of US and euro area equity prices to a global risk-off shock. The shock is identified in a daily Bayesian vector 
autoregression (BVAR) model by Brandt et al.* and calibrated to a flight-to-safety impact of around -10 basis points on the ten-year US Treasury yield. Impulse 
responses are shown after one week and are estimated by local projections allowing for state dependence, similar to the approach in Ramey and Zubairy**, with 
the gamma parameter assumed to be 2. The estimation controls for economic activity, interest rates, funding conditions and stock market uncertainty in the 
United States and the euro area respectively (measured by the Citigroup Economic Surprise Index, the spread between the ten-year and the two-year bond 
yield, financial conditions index and the stock market implied volatility) and includes a crisis dummy for the weeks of the peak of the global financial crisis and 
COVID-19 turmoil. The states are defined based on the US and euro area interest rate market uncertainty, as measured by the MOVE and SMOVE respectively. 
*) Brandt, L., Saint Guilhem, A., Schröder, M. and Van Robays, I., “What drives euro area financial market developments? The role of US spillovers and global 
risk”, Working Paper Series, No 2560, ECB, 2021. 
**) Ramey, V.A. and Zubairy, S., “Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data”, Journal of Political Economy, 
Vol. 126, No 2, 2018, pp. 850-901. 

Elevated implied interest rate market volatility could point to downside macro-financial risks 
that equity investors do not seem to have fully priced in. Risks surrounding the economic outlook 
and the related monetary policy response remain elevated, against the background of rising 
geopolitical risks. These factors explain why implied interest rate market volatility is elevated and, in 
contrast to low option-implied equity market volatility, might signal prevailing financial stability risks. 
Historically, elevated implied interest rate volatility has been associated with larger downside risks to 
economic growth around one year ahead in particular (Chart C, panel b).14  Empirical evidence also 
suggests that equity prices tend to respond more strongly to global risk-off shocks when implied 

13    For a more detailed discussion on risks from 0DTE options, see, for example, the box entitled “The risks 
from hidden leverage in short-term equity options”, Financial Stability Review, ECB, November 2023. 

14    A similar argument is made by Sarisoy, C., “Elevated Option-Implied Interest Rate Volatility and 

Downside Risks to Economic Activity”, FEDS Notes, Board of Governors of the Federal Reserve System, 
22 December 2023. 

Financial Stability Review, May 2024 – Financial markets 

42 

 
 
 
 
 
 
interest rate volatility is elevated (Chart C, panel c). This implies that equity prices could be 
particularly vulnerable to shifts in risk appetite or other adverse shocks in the current environment of 
elevated implied interest rate volatility. 

Low implied equity market volatility could mask financial stability vulnerabilities. Low realised 
and implied volatility in financial markets can support financial stability to the extent that it properly 
reflects sound fundamentals and a stable risk outlook. However, subdued implied equity market 
volatility – despite broader uncertainties related to the macroeconomic outlook and heightened 
geopolitical risks, as reflected in elevated implied interest rate volatility – might suggest an 
underestimation of risks in equity markets and excessive risk-taking.15  Consequently, adverse 
economic surprises or geopolitical shocks could lead to significant market corrections. Large 
exposures in volatility instruments could, in turn, increase the likelihood of a disorderly correction. 

2.3 

Exogenous risks could add to volatility in euro area 
markets 

Risks from the US Treasury market might spill over to euro area markets. Since 
the onset of higher inflation in 2021, implied volatility in interest rate markets has 
increased substantially, undermining the liquidity of the US sovereign bond market 
(Chart 2.9, panel a). In addition, the regulatory reforms implemented in response to 
the global financial crisis have constrained banks’ market making capacity, while the 
supply of government bonds has continued to grow.16  This combination of cyclical and 
structural factors adversely affecting market liquidity has increased the likelihood and 
magnitude of price dislocations, attracting some non-bank financial institutions which 
saw this as an arbitrage opportunity (Box 3). Although such activity is, in principle, 
beneficial for market efficiency, a forced unwinding of leveraged exposures at a time of 
severe market stress might add to volatility, as is believed to have been the case in 
March 2020. That said, conditions in the US Treasury market remain fragile and, given 
the role of these securities as global risk-free assets, the risk of spillovers to euro area 
markets remains high.17 

Growing US debt sustainability concerns might increase financial market 
volatility. The rapid tightening of monetary policy substantially increased the US 
government’s net interest payments not only nominally, but also in relation to budget 
revenues (Chart 2.9, panel b). The expected further growth of these expenses has 
increased concerns about US debt sustainability, as reflected in a number of negative 
rating actions and in market-based measures of US credit risk, such as CDS spreads. 
On the basis of its long-term projections, the US Congressional Budget Office has 

15    See also, for example, “The Volatility Paradox: Tranquil Markets May Harbor Hidden Risks”, Markets 

Monitor, Second Quarter 2017, Office of Financial Research, 2017. 

16    See, for example, Duffie, D., Fleming M., Keane, F., Nelson, C., Shachar, O. and Van Tassel, P., “Dealer 
Capacity and U.S. Treasury Market Functionality”, Staff Reports, No 1070, Federal Reserve Bank of New 
York, August 2023, and Bruno, S. and Hill, A., “Liquidity and resilience in the core European sovereign 
bond markets”, ICMA, March 2024. 

17    See, for example, the box entitled “US Treasury market conditions and global market reactions to US 

monetary policy”, Economic Bulletin, Issue 8, ECB, 2023. 

Financial Stability Review, May 2024 – Financial markets 

43 

 
 
 
 
indicated that unabated future increases in debt could slow economic growth, push up 
interest payments to foreign holders of US debt and pose significant risks to the fiscal 
and economic outlook.18  Although a technical default on outstanding debt would be an 
extreme tail risk, a significant rise in US Treasury bond yields or an induced economic 
shock could weigh on other assets globally. 

Chart 2.9 
Conditions in the US Treasury market remain challenging, while US debt sustainability 
concerns may add to volatility 

a) Volatility and liquidity conditions in the US 
Treasury market 

b) CDS spread on US debt and net interest 
payments as a share of US budget revenues   

(Jan. 2019-May 2024, index) 

(Jan. 2019-Apr. 2024; left-hand scale: basis points, right-hand 
scale: percentages) 

Sources: Bloomberg Finance L.P., US Congressional Budget Office and ECB calculations. 
Notes: Panel a: the latest observations are for 7 May 2024. Implied volatility shows the MOVE index, while illiquidity is proxied by the 
Bloomberg Liquidity Index for US Treasuries. Panel b: the dotted line shows the US Congressional Budget Office’s February projection. 

Although sentiment is buoyant, market participants are trying to weigh up 
geopolitical risks. Since the beginning of the unjustified Russian invasion of Ukraine, 
investors have increased their attention to geopolitical risks, as reflected by the 
frequency at which the topic is mentioned in corporate calls with market participants 
and analysts (Chart 2.10, panel a). The risk of the conflict escalating has also been 
reflected in the outperformance of defence sector companies, especially in the euro 
area, where military spending has already risen significantly and is expected to rise 
still further. In addition, gold prices have recently reached all-time highs, likely driven 
by the demand for geopolitical risk hedges. While the immediate market reaction to 
Hamas’ attack on Israel has been quite muted, increased tail risks have also been 
priced in by the energy market, which is often an important channel of geopolitical risk 
contagion (Special Feature A). Risks to crude oil prices are typically skewed to the 
downside, but when geopolitical risks grow this pattern inverts, as reflected by the 
option-implied volatility skewness (Chart 2.10, panel b). That said, the potential 
escalation of international conflicts, especially when they involve or are close to 

18    See “The Budget and Economic Outlook: 2024 to 2034”, US Congressional Budget Office, February 

2024. 

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44 

 
 
 
 
 
important commodity exporters, might increase the risk of negative supply shocks 
substantially. Such a scenario could undermine disinflation efforts and put significant 
pressure on asset valuations. 

Chart 2.10 
Investors are mindful of geopolitical risks which might, for example, increase the 
likelihood of negative supply shocks 

a) Defence sector’s relative performance and 
references to “geopolitics” in corporate calls 

b) Crude oil volatility skewness vs geopolitical 
risk index 

(Jan. 2020-Apr. 2024; left-hand scale: Dec. 2021 = 100, right-hand 
scale: thousands) 

(Jun. 2014-May 2024; index, percentages) 

Sources: Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: ratio of defence sector sub-indices (euro area – UBS EU Defense Spending Index, United States – UBS Defense 
Spending Index) over broad market indices (euro area – EURO STOXX, United States – S&P 500). The total number of references 
includes the word “geopolitics” and Bloomberg-suggested synonyms. Panel b: the latest observations are for 7 May 2024. Volatility skew 
reflects the difference between implied volatility in 1M 5DC and 5DP options on crude oil. “Onset of Russian invasion of Ukraine” refers to 
the change between 17 February and 3 March 2022, while “Hamas’ attack on Israel” refers to the period 6 October to 23 October 2023. 
For the geopolitical risk index, a seven-day moving average version is used.* 
*) See Caldara, D. and Iacoviello, M., “Measuring Geopolitical Risk”, American Economic Review, Vol. 112, No 4, April 2022, pp. 
1194-1225. 

Box 3 
Financial stability risks from basis trades in the US Treasury and euro area government 
bond markets 

Prepared by Claudio Bassi, Felix Hermes, Simon Kördel, Francesca Lenoci, Riccardo Pizzeghello and Andrzej 
Sowiński 

Basis trades are arbitrage strategies which improve market functioning but are subject to 
specific risks, especially when excessively leveraged. Basis trades typically aim to exploit any 
mispricing between the spot price of a security (adjusted for the funding cost until the expiry of a 
futures contract) and its futures price – the difference being called the net basis. In order to do this, an 
arbitrageur needs to simultaneously conclude two opposing trades – one in the futures market and 
the other in the spot market. As the futures contract approaches its maturity, the futures price and the 
spot price converge, arguably making the basis trade return risk-free if held until the futures contract 
expires. In principle, therefore, basis trades are not speculative in nature and should have a beneficial 
impact on market efficiency and liquidity. Given that price dislocations are typically small compared 
with the market value of the relevant security, arbitrageurs often employ high leverage to enhance 
their returns. In the spot market, leverage is employed using repo funding (securities are pledged as 

Financial Stability Review, May 2024 – Financial markets 

45 

 
 
 
 
collateral and the cash received is used to purchase more securities), while in the futures market, 
leverage is synthetic and stems from the obligation to post only a fraction of the nominal exposure as 
margin. This exposes basis trades to funding risks – the inability to roll over repo borrowing at an 
acceptable price – and liquidity risks – the inability to meet margin calls related to futures positions. 
Rapid unwinding of basis trades in response to forced deleveraging, for instance, could add to price 
dislocations. However, such a scenario is less likely for arbitrage strategies and would have less 
impact on prices than would be the case for leveraged directional positions.19 

The build-up of hedge funds’ leveraged exposures in the US Treasury market has given rise to 
financial stability concerns.20  Some evidence from the US Treasury repo market suggests that 
basis trades are behind the growing net short positions of these funds in US Treasury futures 
(Chart A, panel a).21  Over the last two years, the deterioration of US Treasury market liquidity and 
increased volatility (Chart A, panel b) have made price dislocations more frequent and basis trades 
more attractive. In addition, fixed income funds have seen significant inflows and asset managers 
have preferred the futures market over the spot market to build their duration exposure more flexibly. 
This has put downward pressure on the net basis. Hedge funds have stepped in as a “counterparty” 
for those asset managers in the futures market (Chart A, panel a), at the same time buying US 
Treasuries in the spot market and using them as collateral in the repo market to increase leverage. 

Disruptions in the repo market could still force some entities to unwind their basis trades, 
fuelling dislocations in the US Treasury market. The liquidity preparedness of basis traders to 
maintain their futures positions seems better now compared with previous stress events, as traders 
are expected to meet margin requirements that are close to historical highs (Chart A, panel c). This 
limits the maximum leverage deployed in the strategy. Still, disruptions in the repo market could lead 
to the forced unwinding of basis trades. Given the role of US Treasury bonds as global risk-free 
assets, a volatility jump in response to such unwinding may potentially be observed across asset 
classes and jurisdictions, as has been witnessed during some historical stress events.22  The effect 
could be amplified by the high correlation between US Treasuries and euro area government bonds, 
and when the same counterparties are active in both markets. Sufficient liquidity in the spot, futures 
and repo markets in the United States is therefore crucial to contain vulnerabilities globally. 

19    While the funding risk and the risk of a sudden increase in margin requirements are present for both 

leveraged directional trades and arbitrage strategies, another reason for the forced closure of trades are 
the mark-to-market losses on the strategy. Arbitrage strategies incur such losses in the event of deeper 
price divergences between the spot and the futures markets, which might happen if, for instance, other 
arbitrageurs limit their activity. For directional trades, the likelihood of mark-to-market losses is larger, as 
it only takes prices to move into the opposite direction than assumed. In addition, while unwinding of 
arbitrage trades feeds into price divergences, it should not have directional impact, as unwinding also 
means trading into the opposite directions (in the futures and the spot markets). Unwinding of directional 
bets, however, has strong directional impact on the underlying prices and fuels an already ongoing trend, 
making disorderly price movements and volatility spirals much more likely. 

20    See, for example, Avalos, F. and Sushko, V., “Margin leverage and vulnerabilities in US Treasury 

futures”, BIS Quarterly Review, Bank for International Settlements, September 2023. 

21    See, for example, Barth, D., Kahn, R. and Mann, R., “Recent Developments in Hedge Funds’ Treasury 

Futures and Repo Positions: is the Basis Trade ‘Back’?”, FEDS Notes, Board of Governors of the Federal 
Reserve System, August 2023, or Glicoes, J., Iorio, B., Monin, P. and Petrasek, L., “Quantifying Treasury 
Cash-Futures Basis Trades”, FEDS Notes, Board of Governors of the Federal Reserve System, March 
2024. 

22    Some studies, however, question the impact of forced unwinding of basis trades on price dislocations in 
the US Treasury market in March 2020. See, for example, Barth, D. and Kahn, J., “Basis Trades and 
Treasury Market Illiquidity”, OFR Brief Series, Office of Financial Research, July 2000. 

Financial Stability Review, May 2024 – Financial markets 

46 

 
 
 
Chart A 
Growing basis trade activity in the United States might be a symptom of deteriorating liquidity 
conditions, but vulnerabilities are partly mitigated by high margin requirements 

a) Net exposures in US Treasury 
futures, by entity type 

b) Illiquidity and volatility in the US 
Treasury market 

c) Margin requirements in US 
Treasury futures most shorted by 
leveraged funds 

(Jan. 2019-Apr. 2024, USD billions) 

(Jan. 2019-Apr. 2024, indices) 

(1 Jan. 2019-1 Apr. 2024, percentiles) 

Sources: Bloomberg Finance L.P., CME Group, and ECB calculations. 
Notes: Panel a: entity types as reported in CFTC’s weekly Commitments of Traders (COT) Reports, where “Leveraged Funds” are typically hedge funds.* Panel 
b: “Illiquidity” proxied by the Bloomberg US Govt Securities Liquidity Index and “Volatility” by the MOVE Index. Panel c: distribution of margin requirements for 
front-month contracts relative to their market value. For “COVID-19 turmoil” and “Repo market stress”, highest observed margin requirements are shown. 2Y, 5Y 
and 10Y refer to two-year, five-year and ten-year T-Note futures contracts listed on the CBOT exchange. 
*) See “Traders in Financial Futures - Explanatory Notes”, Commodity Futures Trading Commission (CFTC). 

A build-up of hedge fund exposure has also been observed in the euro area government bond 
market, but the size of basis trade activity seems contained. Offshore hedge funds, believed to 
also be involved in basis trades in the United States, have become increasingly present in the euro 
area government bond repo market, with their positions growing up to threefold since the beginning of 
2021 (Chart B, panel a).23  At the same time, these funds have also been active in the euro area 
government bond futures market, albeit to a lesser extent. A strong negative correlation observed 
when matching these positions suggests some short basis trade activity (Chart B, panel b). In other 
words, these funds have mostly taken long futures positions at the same time as borrowing underlying 
bonds in the repo market and presumably short selling them. While the direction of these basis trades 
is the opposite to what has been observed in the US Treasury market, in principle it is subject to 
similar risks. That said, what limits the financial stability implications is the small scale of these trades 
and more balanced net futures positions (Chart B, panel c). This might be reflective of smaller market 
distortions in the euro area government bond market than in the US Treasury market or higher costs 
of arbitraging. Nevertheless, it appears that the growing presence of offshore hedge funds in the euro 
area government bond market is also related to other investment strategies, potentially including 
leveraged directional trades, associated with higher financial stability risks than basis trades. 
Spillovers to the euro area government bond market could be amplified, should these entities face 
liquidity strains in the US Treasury market. 

23    These funds are mostly domiciled in the Cayman Islands. They account for more than half of investment 
funds’ positions on euro area government bond futures and for almost the entire euro area government 
bond repo activity of non-EU investment funds. 

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47 

 
 
 
 
 
 
Chart B 
The increased presence of non-euro area hedge funds in EGB repo and futures markets can be partly 
linked to basis trade strategies 

a) Gross exposures of selected 
offshore hedge funds in EGB repo 
and futures markets 

b) Basis trades of selected 
offshore hedge funds in EGB 
markets, by issuer country 

c) Net exposures of selected 
offshore hedge funds in EGB 
futures market, by issuer country 

(1 Jan. 2021-25 Apr. 2024, € billions) 

(1 Jan. 2021-25 Apr. 2024, € billions) 

(1 Jan. 2021-25 Apr. 2024, € billions) 

Sources: ECB (EMIR, SFTDS), sector enrichment based on Lenoci and Letizia* and ECB calculations. 
Notes: “Selected offshore hedge funds” refers to investment funds domiciled in the Cayman Islands. EGB stands for euro area government bond. Panel a: 
“Repos” refers to the sum of repo and reverse repo exposures. Repo and reverse repo positions are at the counterparty and collateral level. “Futures” refers to 
the sum of absolute net long and net short positions at counterparty and contract level. Panel b: negative exposures in the repo market indicate borrowing of the 
collateral that is eligible for delivery for the corresponding position in the futures contract. Smaller absolute values on average for repo exposures in comparison 
with the corresponding futures positions might stem from the lack of data on securities financing transactions concluded between selected offshore hedge funds 
and non-EU entities, which might also be the lenders of the relevant bonds. Total reflects aggregated exposures in bonds issued by all three countries listed. 
Panel c: the sample of EGB futures includes futures on German, French and Italian government bonds traded at Eurex, which is the most traded and liquid EGB 
futures market. Futures positions are netted at counterparty and contract level. 
*) See Lenoci, F.D. and Letizia, E., “Classifying Counterparty Sector in EMIR Data”, in Consoli, S., Reforgiato Recupero, D. and Saisana, M. (eds.), Data Science 
for Economics and Finance, Springer, Cham, 2021. 

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3 

Euro area banking sector 

3.1 

Profitability peaked at multi-year highs as headwinds to 
income strengthen 

Euro area bank profitability peaked in the second half of 2023, as cost 
pressures intensified and operating profits weakened. Annual bank profitability 
reached a high of 9.3% in 2023, a level last seen before the global financial crisis. 
However, significant institutions already saw their four-quarter trailing return on equity 
(ROE) decline slightly in the final quarter of the year compared with the previous 
quarter. The turn in profitability is made all the clearer by quarterly data, as the 

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49 

 
 
 
annualised quarterly ROE fell to 7.6% in the fourth quarter of 2023 from a peak of 
10.6% in the second quarter (Chart 3.1, panel a)24. This decline was broad-based, 
driven by rising operating expenses, lower operating income and higher loan-loss 
provisions (Chart 3.1, panel b). As a further indicator of increasing challenges to cost 
control, the weighted average quarterly cost/income ratio of euro area banks 
increased significantly in the fourth quarter of 2023, to 61%, returning to levels 
observed one year ago (Chart 3.1, panel c). This reflects a quarterly increase of 13% 
in operating expenses, including an increase of 14% in staff costs. This sharp 
quarterly increase might, however, reflect some seasonality, as costs increased more 
moderately compared with the fourth quarter of 2022, with quarterly operating and 
staff costs rising by 4.2% and 6.2% respectively year on year. This compares with 
euro area inflation and wage growth of 2.9% and 4.5% respectively in 2023 
(Chapter 1). 

Chart 3.1 
Bank profitability has declined somewhat from multi-year highs over the last six 
months, driven by a rising cost/income ratio and higher loan-loss provisions 

a) ROE of significant 
institutions 

(Q4 2021-Q4 2023, percentages) 

b) Drivers of changes in 
significant institutions’ 
annualised quarterly ROE 

(Q2 2023, Q4 2023; percentages, 
percentage points) 

c) Cost/income ratios of 
significant institutions 

(Q4 2021-Q4 2023, percentages) 

Sources: ECB (supervisory data) and ECB calculations. 
Notes: Panels a and c: based on a balanced sample of 80 euro area significant institutions. Panel b: based on annualised quarterly 
figures. 

Significant institutions’ net interest income stagnated in the fourth quarter of 
2023, amid early indications that interest margins might be narrowing. After 
increasing steadily in the eight preceding quarters, euro area banks’ net interest 
income ceased to grow during the fourth quarter. Lower loan volumes have fully offset 
the positive contribution of expanding net interest margins (NIMs) (Chart 3.2, panel a). 
However, NIMs typically trail developments in loan-deposit spreads charged by banks. 

24    The Financial Stability Review uses the four-quarter average of stock variables, while flow variables are 
annualised using trailing four-quarter sums. In addition, a balanced sample of currently 80 banks is used 
to avoid composition effects, which might result in figures that differ from those published in the 
Supervisory Banking Statistics. 

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50 

 
 
 
 
 
 
These spreads started to decline during the fourth quarter, indicating that NIMs may 
follow suit in the near future (Chart 3.2, panel b). 

Chart 3.2 
Net interest income growth stagnated as loan volumes declined while interest rate 
spreads started to tighten 

a) Quarterly changes in net interest income of 
euro area banks 

b) Interest rate spreads and net interest 
margins of euro area banks 

(Q4 2021-Q4 2023, percentages) 

(Jan. 2016-Mar. 2024, percentage points, percentages) 

Sources: ECB (supervisory data, MIR) and ECB calculations. 
Notes: Panel a: NII stands for net interest income; NIM stands for net interest margin, calculated as net interest income divided by total 
assets. The chart shows quarter-on-quarter changes in NII. Based on a balanced sample of 80 euro area significant institutions. Panel b: 
based on all euro area banks. 

Weak loan demand and tight credit standards suggest that loan growth will 
remain subdued. Rates charged by banks on new loans to households and 
non-financial firms have already lost momentum over recent months and appear to 
have reached their peak (Chart 3.3, panel a). Year-to-date bank lending flows to the 
non-financial private sector were at record lows at the end of March, driven by large 
reductions in mortgage lending and loans to non-financial corporations (NFCs) (Chart 
3.3, panel b). Banks have tightened their credit standards further since the previous 
issue of the Financial Stability Review was published and expect those standards to 
tighten again over the second quarter of 2024, which should further dampen loan 
growth over the medium term. At the same time, the demand for loans from 
households and NFCs has weakened further but is expected to recover slightly during 
the second quarter of 2024 (Chart 3.3, panel c). 

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51 

 
 
 
 
Chart 3.3 
Bank loan rates have peaked amid weak lending dynamics and tightening credit 
standards 

a) Policy rate and bank loan 
rates on new business 

b) Year-to-date bank lending 
flows, to March 

c) Demand for loans to 
households and NFCs and 
lending standards 

(Jan. 2021-Apr. 2024, percentages) 

(2004-24, € billions) 

(Q1 2004-Q2 2024, net percentages) 

Sources: ECB (MIR, BSI, BLS) and ECB calculations. 
Notes: Panel a: DFR refers to the ECB’s deposit facility rate. HH stands for households. Panel b: lending flows correspond to flows for 
January-March for each year. Panel c: “Actual” values are changes that have occurred, while “expected” values are changes anticipated 
by banks. For credit standards, net percentages are defined as the difference between the sum of the shares of banks responding 
“tightened considerably” and “tightened somewhat” and the sum of the shares of banks responding “eased somewhat” and “eased 
considerably” in the ECB’s bank lending survey (BLS). Net percentages for the questions on demand for loans are defined as the 
difference between the sum of the shares of banks responding “increased considerably” and “increased somewhat” and the sum of the 
shares of banks responding “decreased somewhat” and “decreased considerably”. Net percentages have been aggregated by taking the 
weighted average across the three loan categories. 

Floating-rate assets could weigh on banks’ interest income, as market 
reference rates are expected to fall. Three-quarters of the increase in banks’ 
interest income from loans can be linked to loans remunerated at variable rates. This 
is because these loans repriced alongside rising market reference rates while rate 
dynamics for fixed-rate loans have remained comparably muted (Chart 3.4, panel a). 
However, floating-rate loans become a headwind for bank profitability under 
assumptions of an imminent turn in market reference rates, as implied by current 
market expectations. Similarly, banks’ liquid assets, such as central bank reserves, 
reverse repos and short-term debt securities, have been a major source of increased 
profits, but their yields would shrink quickly once market interest rates fell. Banking 
systems with large shares of floating-rate loans and liquid assets are the most 
exposed to declining market reference rates, including several countries where almost 
the entire loan book to NFCs has been granted at variable rates (Chart 3.4, panel b). 

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Chart 3.4 
Variable-rate loans have been the main driver of increases in banks’ loan interest 
income but would become a headwind to profits if market interest rates fall 

a) Euro area bank interest income contributions and lending 
rates on fixed- and floating-rate loans to households and 
NFCs   

b) Share of variable-rate bank 
lending to NFCs, by country 

(left graph: Dec. 2021, Mar. 2024, € billions; right graph: Jan. 2019-Nov. 2025, 
percentages) 

(Feb. 2024, percentages) 

Sources: Bloomberg Finance L.P., ECB (MIR, BSI, AnaCredit) and ECB calculations. 
Notes: Panel a: based on all euro area banks. Interest income is computed as the product of outstanding loan amounts and 
corresponding interest rates and refers to loans to households and NFCs. Average outstanding rates are shown for floating- and 
fixed-rate loans. Panel b: lending shares refer to outstanding amounts for NFC loans. “Fixed” indicates a rate known with certainty to both 
sides of the loan contract at inception. “Variable” indicates a rate linked to an exogenous parameter (e.g. EURIBOR). “Mixed” indicates a 
combination of fixed and variable rates. 

3.2 

Bank funding costs have continued to increase 

Since the monetary policy tightening cycle started, bank liabilities have 
repriced at higher rates, with the degree of pass-through varying across 
different funding sources. Banks’ average cost of funds reached 2.6% in the fourth 
quarter of 2023, an increase of 2 percentage points since the start of the hiking cycle. 
Interest rates have risen for all types of funding, but especially for liabilities with other 
financial institutions, central bank funding and bonds. Even the rate on household 
deposits has increased substantially, by about 1 percentage point, despite exhibiting 
the lowest interest rate sensitivity (Chart 3.5, panel a). 

At the same time, the composition of bank funding has shifted towards more 
expensive instruments. Euro area banks’ liabilities decreased by €508 billion 
between June 2022 and January 2024. The mild aggregate reduction masks a major 
change in composition. Banks repaid €1.7 trillion in central bank funding, and their 
overnight NFC deposits declined by €1.1 trillion. By contrast, term deposits and bonds 
gained importance in the composition of banks’ funding, increasing by a total of €2.4 
trillion, in an overall shift towards more expensive sources of funding (Chart 3.5, 
panel b). Euro area banks have also been transferring government bonds freed up 
from the collateral pool at the ECB to secure repo borrowing. The resulting rise in 
overall funding costs was mainly driven by rising interest rates, while the shift towards 

Financial Stability Review, May 2024 – Euro area banking sector 

53 

 
 
 
 
more expensive funding sources only contributed to a small extent25  (Chart 3.5, 
panel c). 

Chart 3.5 
Funding repricing and composition shift have driven bank funding costs higher 

a) Average funding costs of 
bank liabilities 

b) Cumulative flows of bank 
liabilities 

c) Decomposition of changes 
in bank funding costs 

(Q2 2018-Q4 2023, percentages) 

(July 2022-Mar. 2024, € trillions) 

(Q2 2022, Q4 2023; percentages, 
percentage points) 

Sources: ECB (BSI, supervisory data) and ECB calculations. 
Notes: Panel a: funding costs refer to average rates computed as interest expense/average stock of liability for the quarter. Panels a and 
c: based on a balanced sample of 80 euro area significant institutions. Panel b: based on all euro area banks. 

The outlook for deposit rates remains uncertain, as new business deposit rates 
lose momentum while rates on the outstanding stock continue to rise. With 
policy rates expected to fall and the pass-through of changes in policy rates at similar 
levels to previous hiking cycles, term deposit rates are likely to decline going forward. 
The cost of new term deposits from NFCs has already reached a plateau, and rates 
offered on new term deposits from households already started falling in November 
2023. This contrasts with the evolution of overnight deposit rates, for which the 
pass-through of policy rate increases remains compressed and which continue to rise 
slowly (Chart 3.6, panel a). Moreover, the share of overnight deposits remains high by 
historical standards and depositors continue to move funds into better remunerated 
term deposits. The implications for aggregate deposit rates are uncertain but if historic 
regularities from previous hiking cycles were to be repeated, deposit costs on the 
stock of outstanding deposits could, on average, increase further and lag the turn in 
the short-term interest rate cycle (Chart 3.6, panel b). This implies that deposit costs 
could become a headwind for bank profitability going forward, especially for those 
banks most dependent on deposit funding, such as those with small reserve ratios 
which have already seen larger changes in deposit rates over recent months. 

25    It should be noted that this does not separate the rate effect from the composition effect for shifts from 
overnight deposits to term deposits. Calculations based on ECB (MIR, BSI) data suggest that for NFC 
deposits, this effect accounts for about 15% of the increase in funding costs. 

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Chart 3.6 
The outlook for bank deposit rates is uncertain as market rates have likely peaked 

a) New business deposit rates and betas 

b) Deposit rates and historic and 
market-implied overnight rates 

(Jan. 2022-Apr. 2024, percentages) 

(Jan. 2003-Feb. 2026; percentages) 

Sources: Bloomberg Finance L.P., ECB (MIR, BSI) and ECB calculations. 
Notes: Panel a: deposit betas capture the percentage pass-through of the increase in the ECB’s deposit facility rate (DFR) to new 
business deposit rates since the start of the respective hiking cycles. All three deposit types – overnight, redeemable and term deposits 
– are considered in the right graph. Panel b: EONIA/€STR refers to EONIA minus 8 basis points until end-2021 and €STR afterwards. 

Market-based funding costs have decreased since the previous issue of the 
Financial Stability Review was published, with credit spreads tightening 
considerably for the riskiest instruments. The cost of issuing new debt has risen 
significantly since the start of the monetary policy hiking cycle. Bond yields have, 
however, declined since the previous issue of the Financial Stability Review was 
published, benefiting from expectations of monetary policy rate cuts, which affect the 
yield curve, and strong bank fundamentals which supported a reduction in credit 
spreads (Chart 3.7, panel a). Despite some volatility in the market for covered bonds 
secured on commercial property loans in early 2024, there have been no spillovers to 
broader bank funding markets. Tighter credit spreads created a window of opportunity 
for some issuers to front-load issuance in early 2024. As a result, year-to-date 
cumulative issuance volumes are close to record levels (Chart 3.7, panel b). Market 
analysts expect the strong issuance activity to continue in 2024 – especially across 
covered and senior segments, which offer tighter pricing relative to other debt 
instruments – due to continued TLTRO repayments. In addition, with sizeable 
redemptions looming, issuance of AT1 instruments is also expected to increase 
considerably over previous years. By contrast, the issuance of senior non-preferred 
bonds is expected to slow, as banks have already built out MREL buffers to required 
levels. 

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55 

 
 
 
 
Chart 3.7 
Bank bond spreads have narrowed and issuance activity is close to record levels 

a) Bank bond spreads 

b) Year-to-date euro area bank bond issuance 
volumes, to 7 May 

(3 Jan. 2022-7 May 2024, basis points) 

(2010-24, € billions) 

Sources: S&P Dow Jones Indices LLC and/or its affiliates, Dealogic and ECB calculations. 
Notes: Based on a sample of euro area banks that issue euro-denominated bonds. AT1 stands for Additional Tier 1 securities; T2 stands 
for Tier 2 securities; NPS/HoldCo stands for senior non-preferred securities. Panel a: secondary market z-spreads. Panel b: year-to-date 
issuance volumes until 2 April across years and including issuance in all currencies. 

Bank funding costs are expected to increase further, despite favourable 
developments in market funding conditions. With interest rates expected to 
decline, market-based short-term liabilities, such as those with financial institutions, 
should reprice downwards swiftly, reversing rate effects. By contrast, longer-term 
market-based liabilities, such as bonds, should continue to reprice at higher rates, 
given that outstanding bond rates are still below current market yields. In conjunction 
with the low and lagged pass-through of policy rates to deposit rates, overall funding 
costs might increase further, despite the easing of funding pressures. 

3.3 

Asset quality is slowly deteriorating, with commercial real 
estate and low provisioning levels most concerning 

Non-performing loan (NPL) ratios remain close to historical lows in aggregate, 
but loans to micro firms and the commercial real estate (CRE) sector, and loans 
in countries with historically low NPL ratio levels, are starting to show mild 
signs of deterioration. NPL ratios remain broadly unchanged, apart from a recent 
slight increase for CRE portfolios (Chart 3.8, panel a). This development reflects the 
recent downturn in several CRE markets, in both the euro area and other advanced 
economies. NPL ratios also increased throughout 2023 for lending to micro firms, 
while declining slightly for lending to larger enterprises (Chart 3.8, panel b). This 
divergence in asset quality can be attributed to the effect of a cooling economy over 
the previous quarters, which disproportionately affects smaller firms. Banks in 
countries where NPL ratios have been lower historically are now showing an uptick in 

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56 

 
 
 
 
their NPL ratios, while banks established in countries with historically high NPL ratios 
continued to reduce their stock of legacy NPLs and maintained stable NPL ratios 
(Chart 3.8, panel c).26 

Chart 3.8 
NPL ratios started to increase slightly for loans backed by CRE, loans to micro firms 
and in countries with historically low NPL levels 

a) NPL ratios by sector 

b) NPL ratios of NFC loans by 
firm size 

c) NPL ratios, by country 
group 

(Q1 2020-Q4 2023, percentages) 

(Q1 2020-Q4 2023, exposure-weighted NPL 
ratio of all NFC loans, percentages) 

(Q1 2020-Q4 2023, exposure-weighted 
NPL ratio, percentages) 

Source: ECB (AnaCredit, supervisory data). 
Notes: Panel a: based on the full sample of significant institutions. Excludes loans held for sale, cash and cash balances at central banks 
and other demand deposits. CONS stands for consumer loans; CRE stands for commercial real estate; RRE stands for residential real 
estate. Panel b: AnaCredit follows the EU Commission standard classification for micro, small, medium and large firms. Panel c: based 
on the full sample of significant institutions. Excludes loans held for sale, cash and cash balances at central banks and other demand 
deposits. For country groupings, see footnote 26. Slovakia has only branches or subsidiaries with a parent in the euro area, which are not 
considered here. 

Default rates have started to rise across various sectors from very low levels, 
while early arrears have increased, particularly for CRE and consumer loans. 
Default rates on corporate and retail exposures have been rising since the beginning 
of 2023, suggesting heightened risk in these sectors (Chart 3.9, panel a). Despite 
credit standards tightening and the cost of borrowing rising over the same period 
(Chapter 1 and Box 1), default rates remain at very low levels overall. There is a 
lagged relationship between economic growth and asset quality, and GDP growth is 
expected to strengthen in the second half of 2024, albeit at very different rates across 
countries (Chapter 1), in the light of which default rates are likely to deteriorate in 
countries with weak expected growth. Yet, the recent downturn in the CRE market is 
already affecting the performance of banks’ CRE loan portfolios. Loans less than one 
year in arrears continued to increase in 2023, albeit remaining below pre-pandemic 
levels (Chart 3.9, panel b). On the household side, the higher cost of living and 

26    Countries are grouped based on whether their historical NPL ratio levels are above or below the median 
across countries in the first quarter of 2019. The countries with low historical NPL ratios are Belgium, 
Germany, Estonia, Latvia, Lithuania, Luxembourg, the Netherlands, Austria and Finland. The countries 
with high historical NPL ratios are Ireland, Greece, Spain, France, Italy, Cyprus, Malta, Portugal and 
Slovenia. 

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borrowing is beginning to weigh on consumers, as seen in the growing share of 
consumer loans overdue by less than a year. Loans past due are nearing 
pre-pandemic levels, suggesting an uptick in financial stress (Chart 3.9, panel c). 
Looking forward, more defaults are to be expected in countries where weak economic 
growth forecasts materialise and in sectors, notably CRE, where the downturn 
intensifies. 

Chart 3.9 
Bank asset quality is gradually weakening, which is visible in rising default rates and 
arrears on consumer and CRE loans 

a) Default rates, by sector 

b) Share of CRE loans that are 
less than one year past due 

c) Share of consumer loans 
that are less than one year 
past due and cost of 
borrowing 

(Q1 2019-Q4 2024, percentages) 

(Q1 2019-Q4 2023, percentages) 

(Q1 2019-Q4 2023, percentages) 

Sources: ECB (ECB staff macroeconomic projections for the euro area, March 2024, MIR, supervisory data). 
Notes: Panel a: based on IRB-reporting significant institutions. Four-quarter trailing figures. Euro area exposures only. Panel b: based on 
the full sample of significant institutions; Panel c: based on the full sample of significant institutions. The cost of borrowing is measured as 
the lending rate on new consumer loans to households. 

CRE lending has been at the centre of asset quality deterioration, although it 
remains a small part of banks’ overall lending portfolios. A handful of banks have 
recently experienced a significant deterioration in their CRE portfolios, evidenced by 
large net inflows to NPLs relative to the stock of performing CRE loans (Chart 3.10, 
panel a). While the situation varies considerably across banks, in aggregate CRE 
portfolios have experienced net inflows to NPLs over the last four quarters. The 
deterioration is particularly severe in the United States, whereas the performance of 
euro area CRE loans worsened only slightly (Chart 3.10, panel b). It is important to 
note that US CRE exposures are concentrated among a few banks, but euro area 
banks in aggregate have only limited exposures to US CRE (ten times smaller than 
euro area CRE exposures). Looking ahead, banks expect CRE loan demand to 
decline in the first two quarters of 2024, albeit much less so than in previous quarters, 
possibly indicating a gradual easing of the downturn in the CRE market (Chart 3.10, 
panel c). CRE loans remain a relatively small part of banks’ loan books, accounting for 

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only around 8% of the total loans granted by significant institutions in the fourth quarter 
of 2023. 

Chart 3.10 
A few banks had large net inflows to NPLs on their CRE portfolios recently, while NPL 
ratios deteriorated on US exposures; banks expect CRE loan demand to decline 
further 

a) Distribution of quarterly 
NPL net flows relative to the 
stock of performing loans for 
CRE loans across banks 

b) NPL ratio, by 
country/region of CRE 
exposure 

c) Credit standards, credit 
terms and loan demand for 
CRE loans 

(Q3 2020-Q4 2023, percentages) 

(Q1 2019-Q4 2023, percentages) 

(Q2 2020-Q2 2024, net percentages) 

Source: ECB (supervisory data, BLS). 
Notes: Based on the full sample of significant institutions. Panel a: excludes loans held for sale. Boxplot whiskers extend to the most 
extreme data point, which is no more than 1.5 times the length of the box away from the box. Panel b: loans and advances to NFCs 
collateralised by commercial immovable property. Panel c: each data point corresponds to the previous six-month period. The full lines 
represent the six-month backward-looking values, while the dotted lines show the six-month forward-looking value for Q2 2024. The net 
percentage of banks reporting a tightening of credit standards/terms and conditions is the share of banks reporting a tightening minus the 
share of banks reporting an easing, while the net percentage of banks reporting an increase in loan demand is the share of banks 
reporting an increase minus the share of banks reporting a decrease. 

Banks’ muted provisioning flows could pose a risk if the deterioration in asset 
quality and credit risk continues. At the start of the pandemic, impairments due to 
credit risk eroded large parts of excess CET1 capital in the banking sector (Chart 
3.11, panel a, left graph). If economic conditions, and collateral values in particular, 
trigger further impairments, this could substantially reduce excess CET1 capital. 
Furthermore, NPL coverage has been declining for all loan portfolios since 2018 
(Chart 3.11, panel a, right graph) as banks have disposed of legacy NPLs with 
relatively high coverage ratios. Late and low provisioning could pose a risk if the 
economic environment deteriorates further. As NPL valuations reflect banks’ expected 
recoveries, which largely come out of collateral, the ongoing decline in loan 
impairment flows (Chart 3.11, panel b) seems inconsistent with falling property prices. 
The frequency at which banks revalue collateral varies substantially across the euro 
area27  and the falling valuations suggest that provisioning can be expected to catch 

27    See Horan, A., Jarmulska, B. and Ryan, E., “Asset prices, collateral and bank lending: the case of 

Covid-19 and real estate”, Working Paper Series, No 2823, ECB, 2023. 

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up − translating into a higher cost of risk − and may, in some cases, lead to erosion of 
capital. 

Chart 3.11 
Credit risk impairments could reduce CET1 capital, while NPL coverage ratios and 
banks provision flows declined recently, despite a drop in real estate prices 

a) Net impairments due to credit risk per 
quarter relative to excess CET1 capital, by 
sector; NPL coverage ratio levels and 
cumulative changes 

b) Four-quarter trailing impairment flows, by 
stage, and real estate price growth 

(left graph: Q4 2018-Q4 2023, percentages; right graph: bar: Q4 
2023, left-hand scale: percentages; dot: Q1 2018-Q4 2023, 
right-hand scale: percentage points) 

(Q4 2018-Q4 2023; left-hand scale: € billions, right-hand-scale: 
percentages)   

Sources: Eurostat and ECB (RESR) and ECB (supervisory data, RESC). 
Notes: Based on the full sample of significant institutions. Panel a, left graph: impairments include changes due to change in credit risk 
(net), changes due to modifications without derecognition (net) and changes due to an update in the institution’s methodology for 
estimation (net). CET1 surplus/deficit refers to the difference between actual CET1 capital and regulatory requirements. Right graph: the 
NPL coverage ratio is computed as the stock of loan-loss provisions divided by the amount of NPLs. The bars show the level of NPL 
coverage ratio in Q4 2023, while the dots show the cumulative decline between Q1 2018 and Q4 2023. CONS stands for consumer 
loans; CRE stands for commercial real estate; RRE stands for residential real estate, SME stands for small and medium-sized 
enterprise. Panel b: excludes outflows for disposals and write-offs. The lines represent annual percentage changes in CRE and RRE 
prices. 

3.4 

Resilient banks amid subdued market valuations 

Euro area banks continue to display resilience as liquidity positions and 
solvency ratios, supported by organic growth from high bank profitability, 
remain robust overall. The aggregate liquidity coverage ratio (LCR) of significant 
institutions in the euro area rose above 160% in the fourth quarter of 2023, despite the 
repayment of more than 80% of borrowed targeted longer-term refinancing operation 
(TLTRO) funds over recent quarters (Chart 3.12, panel a). The limited impact on the 
LCR from TLTRO repayments is partly because banks did not rely solely on excess 
reserves to meet TLTRO outflows but also reduced loans on demand28, which do not 
qualify as high-quality liquid assets (HQLA) and thus have no impact on the LCR. 
Furthermore, TLTRO repayments released HQLA back into the banking system, 
which helped to support the LCR. Moreover, LCRs have also benefited from a small 

28  Loans on demand are loans that a lender can require to be repaid in full at any time. 

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reduction in the expected net outflows thanks to the migration of deposits from sight to 
term accounts29  (Chart 3.12, panel b). At 15.33% in the fourth quarter of 2023, the 
aggregate CET1 ratio of euro area banks was 33 basis points higher than one year 
ago, driven by an increase in retained earnings underpinned by strong bank 
profitability (Chart 3.12, panel c).30 

Chart 3.12 
Liquidity and capital positions remain robust despite large TLTRO repayments and 
record shareholder payouts 

a) LCR and composition of 
assets side 

b) Changes in LCR 

c) Annual changes in CET1 
ratio 

(Q1 2017-Q4 2023; left-hand scale: 
€ billions, right-hand-scale: percentages) 

(Q2 2022-Q2 2023, € billions) 

(Q4 2021-Q4 2023; percentages and 
percentage point contributions) 

Sources: ECB (supervisory data) and ECB calculations. 
Notes: Based on a balanced sample of 80 euro area significant institutions. Panels a and b: L1 and L2 stand for level 1 and level 2 
respectively. L1 assets are of the highest quality and liquidity. L2 assets are of lower quality and less liquid than L1 assets, and they are 
subject to limits on the extent to which a bank can hold them to meet the LCR requirement. Panel b: CB stands for central bank. Change 
between Q2 2022 and Q2 2023. 

Looking ahead, analysts expect bank profitability to decline slightly over the 
next two years, albeit to still comfortable levels above historic averages. 
Analysts expect the ROE of listed banks to fall from the present level of 11% to 10.7% 
and 10.4% in 2024 and 2025 respectively (Chart 3.13, panel a). This decline in bank 
profitability is expected to be driven by a mild reduction in net interest margins together 
with a slight rise in the cost of risk (Chart 3.13, panels b and c). 

29    The LCR is calculated by dividing a bank’s HQLAs by its total net cash flows, over a 30-day stress period. 

Total expected cash outflows are calculated by multiplying the outstanding balances of various 
categories or types of liabilities and off-balance-sheet commitments by the rates at which they are 
expected to run off or be drawn down. Term deposits with maturity beyond 30 days have a 0% run-off 
rate, while the run-off rate for overnight deposits is between 3% and 10%. This means that a shift from 
overnight to term deposits has effectively reduced the expected outflows (LCR denominator). 

30    In addition, Pillar 2 requirements increased by an average of 10 basis points in the latest Supervisory 

Review and Evaluation Process, due among other things to heightened liquidity and interest rate risk in 
the banking book. 

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61 

 
 
 
 
 
 
Chart 3.13 
Analysts expect that bank profitability will decline mildly in 2024 and 2025 to still 
comfortable levels, as net interest margins narrow and cost of risk increases 

a) Return on equity 

b) Net interest margin 

b) Cost of risk 

(percentages) 

(percentages) 

(percentages) 

Sources: LSEG and ECB calculations. 
Notes: Based on 37 listed banks with available analyst projections. All items refer to annual data. NIM stands for net interest margin and 
is computed as net interest income divided by total assets; cost of risk is computed as loan-loss provisions divided by total loans. 

Euro area bank valuations lag those of some global peers, reflecting investor 
concerns about the durability of bank profits. The aggregate price-to-book ratio of 
euro area banks has improved in recent months and currently stands at 0.77 (Chart 
3.14, panel a). Notwithstanding the recent improvement, the ratio remains notably 
below 1 and below that of some international peers, reflecting investor concerns about 
the ability of euro area banks to sustain current profitability levels durably given 
headwinds from weaker asset quality, lower revenues and cost of funding. In addition, 
one-off factors such as the introduction of bank levies and lingering structural 
problems across the industry may play a role. However, a track record of strong 
profitability and a low cost/income ratio are important determinants of increased 
price-to-book ratios at the individual bank level, suggesting that sustained bank 
profitability and efficiency provide a path to improved bank valuations (Chart 3.14, 
panel b). 

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Chart 3.14 
Euro area bank price-to-book ratios continue to lag international peers but the 
relationship with bank profitability suggests a path to improving valuations 

a) Price-to-book ratios of euro area banks and 
international peers 

b) Relationship between price-to-book ratios, 
bank efficiency and profitability 

(3 Jan. 2020-3 May 2024, ratios) 

(Q4 2023, percentages) 

Sources: LSEG, Bloomberg Finance L.P., ECB (supervisory data) and ECB calculations. 
Notes: Panel a: price-to-book ratios for Datastream banking sector indices. Panel b: calculations based on sample of 29 listed euro area 
banks. The cost/income and price-to-book ratios are as of Q4 2023. 

Box 4 
Non-bank financial intermediaries as providers of funding to euro area banks 

Prepared by Emanuele Franceschi, Christoph Kaufmann and Francesca Lenoci 

Around 20% of euro area banks’ funding is provided by the non-bank financial intermediation 
(NBFI) sector. Compared with usually more stable retail sources, NBFI funding mainly consists of 
market-based instruments, such as bonds and repurchase agreements, with the latter being 
particularly sensitive to stress events.31  Leveraging on previous analysis,32  this box investigates the 
role of the NBFI sector in providing funding to banks. In this context, the analysis assesses risks to 
banks in the event of sudden outflows from the NBFI sector with potential knock-on effect on their 
ability to finance banks. Specifically, we evaluate whether banks can replace their NBFI funding by 
tapping different instruments or sectors. 

31    The run on repo during the global financial crisis was driven predominantly by outflows from foreign 

banks, hedge funds and the NBFI sector; see Gorton, G.B., Metrick, A. and Ross, C.P., “Who Ran on 
Repo?” AEA Papers and Proceedings, Vol. 110, May 2020. Also, banks and corporates with more 
funding from non-banks were less resilient during the period of acute financial stress in 2020; see 
Forbes, K., Friedrich, C. and Reinhardt, D., “Stress relief? Funding structures and resilience to the covid 
shock”, Journal of Monetary Economics, Vol. 137, July 2023, pp. 47-81. 

32    See the special feature entitled “Key linkages between banks and the non-bank financial sector”, 

Financial Stability Review, ECB, May 2023. 

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Chart A 
The share of NBFI funding has increased since 2021, driven by more bond issuance and repo 
financing 

a) Share of funding from the NBFI sector, by bank 
business model 

b) Cumulative changes in euro area banks’ liabilities 
and share of funding from the NBFI sector 

(Q1 2021-Q3 2023, percentages) 

(2021-23; left-hand scale: € trillions, right-hand scale: percentages) 

Sources: ECB (CSDB, supervisory data, SHS) and ECB calculations. 
Notes: Panel a: box-whisker plots based on a sample of 97 euro area banks, where the boxes indicate the interquartile ranges, the dots indicate the median, and 
the whiskers indicate the 10th and 90th percentiles. AMs stands for asset managers; IB stands for investment banks; G-SIBs stands for global systemically 
important banks. 

The importance of NBFI funding varies with banks’ business models. Investment banks and 
banks specialised in corporate and wholesale lending often receive about one-third of their funding 
from NBFI entities (Chart A, panel a). Universal and diversified banks – which dominate the euro 
area banking sector – and smaller retail banks receive between 5% and 10% of their funding from the 
NBFI sector. Banks which depended significantly on NBFI funding in 2021 have tapped this source 
even more over the last two years, while smaller banks further reduced their initially low exposure. In 
aggregate, the importance of non-bank funding has increased over recent years, with a reduction in 
central bank funding being partially offset by issuing bonds and borrowing from NBFI entities on 
secured money markets (Chart A, panel b). 

NBFI sectors feature preferred habitats for different asset classes and maturities, leading to a 
limited degree of substitutability across sectors and funding instruments. Insurance 
corporations and investment funds hold sizeable amounts of long-term debt securities issued by euro 
area banks (Chart B, panel a).33  Other financial institutions and investment funds provide short-term 
secured funding on repo markets, while money market funds hold large amounts of banks’ 
commercial paper and certificates of deposit. The concentration by funding source reflects different 
business models, investment mandates and maturity profiles in NBFI sectors. 

Short-term repo funding could be particularly volatile during periods of financial stress. 
Econometric analysis finds that about 25% of a reduction in repo funding to a given bank by one of its 
counterparties is replaced by other institutions on the same trading day (Chart B, panel b). However, 

33    Investment funds also hold the largest amounts of banks’ AT1 bonds, compared with other NBFI sectors. 

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reductions in repo funding from the NBFI sector could be challenging for banks to replace, potentially 
forcing them to shrink their balance sheets. For example, a reduction of €1 in repo funding from 
investment funds correlates with a further reduction of €0.26 in repo funding from other, similar 
institutions, after controlling for overall changes in banks’ demand for funding. 

Chart B 
Different NBFI sectors provide different types of bank funding, leading to limited substitutability in the 
event of lower funding supply 

a) Market-based bank funding, by instrument and 
providing sector 

b) Change of bank repo funding after €1 loss of repo 
funding provided by other banks or non-banks 

(Q1 2021, Q4 2023; percentages) 

(point estimates and 90% confidence bands, €) 

Sources: ECB (CSDB, SFTDS, SHS, supervisory data) and ECB calculations. 
Notes: Panel a: ICPFs stands for insurance corporations and pension funds; IFs stands for investment funds; MMFs stands for money market funds; OFIs stands 
for other financial institutions. Panel b: regressions are based on up to 2,900,000 transaction-level observations for repos between 248 euro area banks and all 
counterparty entities using daily observations between January 2021 and December 2023. The dependent variable is the one-day change in total repos provided 
to bank i by all counterparty entities except for entity j. The control variables include the one-day change in repos provided by counterparty j to the bank i as well 
as dummy interactions for different repo providing sectors. The regressions also include bank time fixed effects to control for bank demand for funding as well as 
all other bank and time-specific developments. The coefficients show the joint effect of a change in repo funding provided by other banks, non-banks, and 
investment funds on the total repo funding of bank i. 

Some recent episodes of liquidity turmoil in the NBFI sector led to financial stability issues 
for banks,34  suggesting that more widespread shocks could affect banks’ ability to secure 
funding. NBFI entities play a pivotal role as key sources of funding for banks. All in all, this funding 
has not experienced major systemic stress events over the last few years, despite market shocks and 
banking sector tensions. Nevertheless, a high concentration of NBFI funding in some banks, together 
with NBFI sectoral preferences for specific funding instruments, could make swift substitution difficult 
should funding outflows materialise. In a crisis, uninsured depositors, high-net-worth individuals and 
professional investors are most likely to run. This creates a vulnerability for banks, in particular as 
regards short-term repo funding, although the ability to reuse collateral with other counterparties 
could mitigate these vulnerabilities. Indeed, the turmoil in March 2023 showed that banks facing 
liquidity difficulties can be at risk of failure, even if they comply with regulatory ratios. 

34    In March 2020, for example, high, rapid outflows constrained the funding that money markets could 

provide to banks. In September 2022 the UK mini-budget triggered a sharp fall in gilt prices that affected 
pension funds. In March 2023 the AT1 market froze following the collapse of Credit Suisse. 

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4 

Non-bank financial sector 

4.1 

Fragile macro-outlook may still test non-banks’ resilience 

The non-bank financial intermediation (NBFI) sector in the euro area has 
remained resilient overall and benefited from rising investment income in 2023. 
Euro area non-banks have continued to prove resilient in a challenging 
macro-financial environment (Chapter 1), further adjusting their portfolios towards 
fixed income securities in the context of a higher interest rate environment. Higher 
interest rates have also resulted in rising investment income from debt securities. This 
has allowed non-banks to generate increasing returns while simultaneously reducing 

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their exposures to comparatively riskier asset classes. Although aggregate income 
from both fixed- and variable-rate debt securities has improved for the NBFI sector 
(Chart 4.1, panel a), some sub-sectors, such as insurance corporations, have only 
benefited marginally to date (Section 4.3). 

Chart 4.1 
Higher interest rates have pushed up non-banks’ investment income from debt 
securities, but have so far not translated into higher liquidity buffers 

a) Euro area NBFI sector investment income 
from debt securities 

b) Euro area NBFI sector cash and liquid asset 
holdings 

(Q1 2021-Q4 2023; € billions, percentages) 

(Q1 2021-Q4 2023, percentages of total assets) 

Sources: ECB (ICB, IVF, PFBR, SHS, CSDB) and ECB calculations. 
Notes: Panel a: annualised income as a share of nominal holdings. Fixed-coupon debt securities include zero coupon bonds. Panel b: 
HQLA (high-quality liquid assets) are defined as HQLA Level 1 securities. 

Liquidity buffers have declined further, despite higher returns on more liquid 
asset classes, limiting the capacity of the NBFI sector to absorb shocks. The 
cash and liquid asset holdings of euro area non-banks remain low in aggregate, 
exposing the NBFI sector to liquidity risks (Chart 4.1, panel b). This represents a 
structural vulnerability in open-ended investment funds as it increases the risk of 
forced asset sales in the event of an unexpected rise in shareholder redemptions 
(Section 4.2). Sudden liquidity needs may also arise from margin calls on derivative 
exposures (Box 5), especially for interest rate derivatives amid elevated interest rate 
volatility (Chapter 2). Ensuring adequate preparedness against spikes in demand for 
liquidity therefore remains a key element in preserving financial stability in the NBFI 
sector (Chapter 5). 

NBFI portfolio valuations have been supported by improved market sentiment, 
while equity exposures have become more concentrated. Improved financial 
market sentiment in late 2023 and early 2024, especially in US equity markets 
(Chapter 2), has helped to push up asset valuations in the NBFI sector. Over the 
course of 2023, euro area non-banks’ holdings of listed shares issued by non-financial 
corporations became more concentrated, reflecting both a reduction in overall equity 
portfolio size and an increasing market footprint of a few large issuers. The share of 
the 25 largest issuers held among non-financial equities has risen to 24% for 

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investment funds and 25% for insurance corporations and pension funds (ICPFs) 
(Chart 4.2, panel a). By contrast, portfolio concentration is relatively stable or 
declining for non-financial debt holdings. Equity portfolios may therefore be 
increasingly vulnerable to idiosyncratic risk, especially in investment funds, where 
holdings are additionally concentrated in US-based technology firms (Section 4.2). As 
such, sudden drops in the share price of one or a few individual companies could 
trigger significant portfolio losses and result in fund outflows, with the potential for 
spillovers to the wider financial system. 

Chart 4.2 
Non-banks’ equity portfolios have become more concentrated while the sector also 
remains exposed to geopolitical risk 

a) Euro area NBFI sector investments allocated to the top 25 
non-financial debt and equity issuers held 

b) Euro area NBFI sector 
holdings, by rating and 
exposure to geopolitical risk 

(Q1 2021-Q4 2023; € trillions, percentages) 

(Q4 2023; percentages, € trillions) 

Sources: ECB (SHS, CSDB) and ECB calculations. 
Notes: Panel a: equities are defined as listed shares issued by non-financial corporations. Indirect exposures relate to assets held though 
investment fund shares. Panel b: levels of geopolitical risk exposure are defined at the sector level using the methodology outlined in 
Special Feature A in this issue of the Financial Stability Review. The worst available rating is used to allocate holdings to credit risk 
segments. 

Downside risks to asset valuations remain, especially for NBFI portfolios with 
high credit risk, a focus on real estate or exposures sensitive to geopolitical 
risk. While the overall outlook has improved over the past six months, the 
macroeconomic environment remains characterised by elevated uncertainty 
(Chapter 1). Pockets of vulnerability therefore remain in different parts of the euro 
area NBFI sector, which may still face valuation losses. While a risk of rising corporate 
defaults may impair asset quality for a wide range of NBFI entities, a further downturn 
in real estate markets may particularly affect valuations of real estate investment funds 
or ICPFs with sizeable real estate holdings (Sections 4.2 and 4.3). Investment 
portfolios held by the euro area NBFI sector are also sensitive to increases in 
geopolitical risk, and tensions related to ongoing conflicts and upcoming elections may 
also indirectly spill over to the sector (Special Feature A). The risk of potential 

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valuation losses in this context could thereby be amplified by elevated credit risk in a 
significant share of asset holdings with medium or high levels of sensitivity to 
geopolitical risk (Chart 4.2, panel b). 

4.2 

Funds face risks from concentrated portfolios, real estate 
and low liquidity 

Euro area investment funds’ portfolios have shifted towards safer assets, but 
concerns remain over funds’ support to the euro area real economy. Over the 
last two years, euro area investment funds have rebalanced their portfolios’ holdings 
away from equities towards debt securities, in particular sovereign and financial bonds 
(Chart 4.3, panel a). This shift in funds’ securities holdings highlights a de-risking 
trend. At the same time, concerns remain about the support given to the euro area 
economy by investment funds through the equity markets, which may point to a 
tightening in financing conditions for euro area corporates. Indeed, cumulative flows of 
euro area-domiciled equity funds into euro area stocks have been negative for the last 
two years (Chart 4.3, panel b). At the same time, flows into US stocks have been 
steadily rising. These observed flow dynamics reflect the diverging growth 
expectations between the two economies (Chapter 1, Chart 1.2, panel a), while the 
declining flows towards emerging Asian markets (since the second half of 2023) might 
be echoing the rising geopolitical tensions. 

Concentration in the non-financial equity portfolio of euro area investment 
funds remains high and tilted towards US issuers. The share of holdings in the top 
25 issuers rose from 20% in the fourth quarter of 2022 to 24% in the fourth quarter of 
2023, following a trend common to the rest of the non-bank sector (Section 4.1, 
Chart 4.2, panel a). Within this share, portfolio concentration has shifted significantly 
from euro area issuers towards US issuers over the last decade (Chart 4.3, panel c). 
In terms of sector, technology companies account for more than 60% of the top 25 
issuers as of the fourth quarter of 2023. These factors expose the euro area 
investment fund sector to adverse developments in the US economy and to potential 
bubbles in the technology sector (Chapter 2, Chart 2.6). 

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Chart 4.3 
Euro area investment funds are reducing their equity exposures towards the euro area 
economy and increasing their portfolios’ concentration towards US and tech sectors 

a) Euro area IF transactions of 
security portfolios, by security 
type and issuer sector 

b) Cumulative flows of euro 
area-domiciled equity funds 
into stocks, by region 

c) Exposure of euro area IFs to 
NFC equity of the top 25 
issuers, by country and 
technology sector   

(Q1 2022-Q4 2023, € billions) 

(3 Jan. 2022-7 May 2024, country flows as 
percentages of total country allocation) 

(Q4 2013-Q4 2023; left-hand scale: 
percentages, right-hand scale: € trillions) 

Sources: ECB (CSDB, SHS), EPFR Global and ECB calculations. 
Notes: IFs stands for investment funds. Panel b: country flows combine fund flows and country allocations to show total flows into a 
specific country. Country allocation is the average fund’s exposure to a country, while total country allocation is the total flows into a 
specific country. 

Corrections in real estate markets might challenge the liquidity preparedness of 
real estate investment funds (REIFs). Euro area REIFs might face losses from real 
estate market corrections, as hinted at by the declining market capitalisation of real 
estate investment trusts (REITs)35. The net asset value of euro area REIFs has 
remained stable, despite a significant correction in the underlying commercial real 
estate market, which suggests that valuation losses have not yet been fully priced in 
(Chart 4.4, panel a). Such losses might trigger redemption requests for REIFs, putting 
stress on their cash buffers. Indeed, cumulative quarterly flows into euro area 
open-ended REIFs have been declining since the start of the monetary policy 
tightening cycle and turned negative as of the third quarter of 2023. Moreover, the 
median cash buffer has also gone down (Chart 4.4, panel b). Insufficient cash buffers 
could lead to forced asset sales, particularly if the downturn in the real estate market 
were to persist or intensify. 

35    REITs are structured as companies or trusts which own (sometimes operate) income-producing real 

estate. They are traded like stocks and pay dividends to investors. REIFs, by contrast, invest in public 
real estate companies (which can include REITs) and aim to generate value from the appreciation of the 
securities they own. 

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Chart 4.4 
Corrections in real estate markets and low liquidity buffers could be a test for the 
resilience of euro area investment funds 

a) Cumulative changes in net 
asset value of euro area REITs 
and REIFs 

(Q1 2022-Q4 2023, cumulative percentage 
change in total net asset value) 

b) Euro area open-ended REIF 
cash buffers and net flows 

c) Redemption coverage ratio, 
by type of euro area 
investment fund 

(Q2 2022-Q4 2023, percentages; left-hand 
scale: cash as a share of total net asset 
value, right-hand scale: net flows as a share 
of total net asset value) 

(Q4 2019-Q4 2023, ratio) 

Sources: ECB (IVF), Bloomberg Finance L.P., LSEG Lipper and ECB calculations. 
Notes: REITs stands for real estate investment trusts; REIFs stands for real estate investment funds. Panel b: the distributions are from 
country aggregate statistics of open-ended REIFs. The countries included in the sample are Germany, Ireland, France, Luxembourg, the 
Netherlands, Austria, Portugal and Slovakia. The whiskers refer to the 10th and 90th percentiles. Panel c: the redemption coverage ratio 
(RCR) measures investment funds’ resilience to redemption shocks, following the methodology set out in the box entitled “Assessing 
liquidity vulnerabilities in open-ended bond funds: a fund-level redemption coverage ratio approach”, Financial Stability Review, ECB, 
November 2023. The RCR is obtained by dividing the value of fund-level HQLA stock by net outflows experienced in a severe but 
plausible scenario lasting 30 days. The box plots display the distribution per fund group of the resulting fund-level RCRs. The whiskers 
refer to the 10th and 90th percentiles. 

Liquidity risks and leverage continue to be a challenge for the euro area 
investment fund sector. The redemption coverage ratio (RCR) shows that overall 
the sector is in a position to meet liquidity needs from outflows. However, the ratio has 
deteriorated since the fourth quarter of 2019, and pockets of vulnerabilities lie in the 
lower tails of the RCR distributions, especially for certain types of funds with 
comparatively high liquidity mismatches (Chart 4.4, panel c). Liquidity shocks might 
come from the derivatives market, where the ability of some funds to meet margin calls 
has deteriorated over the last two years (Box 5). Furthermore, excessive leverage 
remains an issue for the investment fund sector, especially when combined with low 
liquidity buffers and high credit risk. These considerations highlight the need to 
strengthen the resilience of investment funds from a macroprudential perspective 
(Chapter 5 and Box 6). 

Emerging risks from private market funds and geopolitical tensions might pose 
new challenges to the euro area’s financial stability. Although still limited in size, 
the euro area private market fund sector has been growing significantly over the last 
two decades (Chart 4.5, panel a). Despite demonstrating a relatively low risk profile 
overall, private markets have concentrated exposures, opaqueness and uncertain 
resilience in a higher interest rate environment that are a source of concern for 
financial stability (Special Feature C). Further worries stem from geopolitical 

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tensions. On the one hand, direct exposures of euro area investment funds to 
countries badly affected by geopolitical risk are limited and decreasing (Chart 4.5, 
panel b). On the other hand, the threat of adverse geopolitical developments may still 
spread to the sector indirectly, increasing uncertainty and undermining investor 
confidence (Special Feature A). 

Chart 4.5 
An expanding private market fund sector and exposures to geopolitical risk might yield 
new challenges for euro area financial stability 

a) Size and composition of the euro area 
private market fund sector 

b) Euro area investment funds’ exposures to 
countries subject to geopolitical risk 

(2000-23; left-hand scale: € trillions, right-hand scale: percentages)  (Q1 2021-Q4 2023; left-hand scale: € billions, right-hand scale: 

percentages) 

Sources: ECB (IVF, SHS, CSDB), PitchBook Data, Inc. and ECB calculations 
Notes: Panel a: data for 2023 refer to Q3. Private equity funds include venture capital funds; real asset funds include real estate, 
infrastructure and natural resources. Panel b: *data for China include Hong Kong SAR and Taiwan. 

Box 5 
Assessing the liquidity preparedness of investment funds to meet margin calls in derivatives 
markets 

Prepared by Margherita Giuzio, Annalaura Ianiro, Fabrizio Lillo36, Valentina Macchiati, Andrzej Sowiński and 
Elisa Telesca 

Recent episodes of liquidity stress in financial markets have highlighted the need to monitor 
the liquidity preparedness of funds to meet margin calls in the derivatives market.37  Spikes in 
margin calls can lead to liquidity strains in the investment fund sector and to procyclical asset sales 
during times of market stress. This scramble for liquidity can spread to other parts of the financial 

36  University of Bologna, Bologna, Italy. 
37    See “Non-banks’ liquidity preparedness and leverage: insights and policy implications from recent stress 
events”, Financial Stability Review, ECB, May 2023; “Lessons learned from initial margin calls during the 
March 2020 market turmoil”, Financial Stability Review, ECB, November 2021; Jukonis, A., Letizia, E. 
and Rousová, L., “The impact of derivatives collateralisation on liquidity risk: evidence from the 
investment fund sector”, Working Paper Series, No 2756, ECB, December 2022; and Ghio, M., Rousová, 
L., Salakhova, D. and Villegas Bauer, G., “Derivative margin calls: a new driver of MMF flows”, Working 
Paper Series, No 2800, ECB, March 2023. 

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system and the real economy, potentially transforming liquidity stress at the individual entity level into 
a system-wide issue, as happened during the market turmoil in March 2020 and the UK gilt crisis in 
September 2022.38  This box proposes four novel indicators of fund-level liquidity preparedness to 
meet margin calls, aimed at identifying potential pockets of vulnerabilities that may require higher 
cash buffers and/or more diversified high-quality liquid assets (HQLA).39 

Over 15% of euro area open-ended investment funds and exchange-traded funds (ETFs) seem 
to be inadequately prepared to cope with plausible spikes in margin calls. The first indicator is 
the ratio of the stock of initial margin posted by these investment funds to their cash holdings. This 
measures the share of these holdings that could be depleted to meet plausible variation margin 
calls,40  making it an ex ante metric aimed at gauging liquidity preparedness against reasonably 
anticipated liquidity needs.41  A ratio above 100% suggests that the cash holdings might not be 
sufficient and that other assets may well need to be sold. The median ratio between the first quarter of 
2022 and the end of 2023 comes in at around only 20%, although it did increase towards the end of 
that period. As of December 2023, around 20% of bond and mixed-asset funds and 10% of equity 
funds had a stock of initial margins amounting to over 80% of their cash holdings (Chart A, panel a). 
This high share can raise some liquidity concerns, as it is similar to that observed in March 2020 when 
a spike in market volatility coupled with large outflows led to significant procyclical asset sales by 
funds. 

In addition, for more than 20% of funds, the actual maximum weekly flow of margins posted in 
a given quarter amounts to over 80% of their cash holdings. The second indicator is the ratio of 
the flow of initial and variation margins posted to cash holdings. It measures how much of the realised 
changes in margin calls could have been covered by cash. As such, it is an ex post metric aimed at 
comparing liquidity preparedness against actual liquidity needs. The realised median margin flows 
amounted to 20% of funds’ cash holdings between 2022 and 2023, but this share started increasing 
towards the end of that period. In the fourth quarter of 2023, around 25% of bond and mixed-asset 
funds posted margins larger than 80% of their cash holdings, mainly due to the increased volatility in 
the bond market following monetary policy tightening (Chart A, panel b). 

38    Stress in the UK gilt market also stemmed from collateral calls in the repo market. See, for example, 

Dunne, P., Ghiselli, A., Ledoux, F. and McCarthy, B., “Irish-Resident LDI Funds and the 2022 Gilt Market 
Crisis”, Financial Stability Notes, Vol. 2023, No 7, Central Bank of Ireland, September 2023. 
39    The post-global financial crisis reforms have greatly increased collateralisation of trading in the 

derivatives market. While this has reduced the counterparty credit risk, it also increased the liquidity 
needs of market participants, especially in times of market stress. 

40    While variation margins are paid in cash, initial margins can also be met with non-cash collateral. 
41    Initial margin requirements aim to cover potential changes in contract valuation in the interval between 

the last margin collection and the liquidation of positions, in case a counterparty defaults. Since they are 
calculated mostly based on the expected volatility of the underlying asset, they are also an objective 
proxy of plausible variation margin calls over the margin period of risk. 

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Chart A 
Euro area investment funds’ cash holdings seem adequate overall to cover variation margin needs, 
but pockets of risk remain in the upper tails 

a) Ratio of initial margins posted to cash holdings 

b) Ratio of margin flows (initial and variation) to cash 
holdings 

(Feb.-Apr. 2020, Q1 2022-Q4 2023; percentages) 

(Feb.-Apr. 2020, Q1 2022-Q4 2023; percentages) 

Sources: ECB (EMIR), EMIR sector enrichment based on Lenoci and Letizia*, LSEG Lipper and ECB calculations. 
Notes: The sample includes euro area-domiciled mutual funds and ETFs reporting in both EMIR and Lipper. The samples considered for 2020 and 2022-23 do 
not overlap completely. “Pandemic” refers to the period between February and April 2020. The whiskers refer to the 15th and 85th percentiles. For confidentiality 
reasons, the percentiles of the distribution are calculated by averaging values across four entities. Panel a: the chart shows the distribution of the maximum over 
the quarter of the ratio of the stock of initial margin posted to cash holdings as at the end of the month, at fund level. Panel b: margins flows are calculated as the 
weekly (Wednesday-Wednesday) difference between the stock of margins defined as the sum of initial and variation margins posted minus variation margins 
received (meaning that outflows have a positive sign). Therefore, margin flows might, by design, suffer from distortions around the contract closure, when the 
stock of related variation margin posted is reset to zero, without a corresponding exchange of cash. The ratio is calculated by first dividing the maximum weekly 
flows over the month by the cash holdings as of the previous month, at fund level, and then taking its maximum over the quarter. Cash posted to meet margin 
requirements is reflected in both the numerator and the denominator of the ratios. 
*) See Lenoci, F.D. and Letizia, E., “Classifying Counterparty Sector in EMIR Data”, in Consoli, S., Reforgiato Recupero, D. and Saisana, M. (eds.), Data Science 
for Economics and Finance, Springer, Cham, 2021. 

As they might not have sufficient cash to cover margin calls, it is important that funds rely on 
diverse and reliable sources of liquidity and collateral.42  The third indicator is the ratio of the 
stock of initial margin posted by funds to their HQLA holdings.43  This gauges the share of HQLA 
holdings that might be needed to meet plausible variation margin calls, and to what extent a buffer for 
any potential increase in the initial margin requirements is already used.44  The median ratio is low, 
with initial margins posted amounting to less than 5% of funds’ HQLA stock (Chart B, panel a). 
Similarly, the final indicator, which sets initial and variation margin flows against HQLA holdings, 
suggests that the realised changes in margin calls could, on average, comfortably be covered by 
HQLA (Chart B, panel b). However, this might not hold true for those funds at the upper tails of the 
distribution, especially bond and mixed-asset funds. In addition, some of the securities included in the 
HQLA holdings may become illiquid in periods of stress, as happened in March 2020. Their resulting 
forced sale to cover margin calls would impact prices quite significantly, which could potentially further 
feed market stress. 

42    See “Liquidity preparedness for margin and collateral calls: Consultation report”, Financial Stability 

Board, April 2024. 

43    The funds in the sample have a quite diverse composition of HQLA stock. For example, in the fourth 

quarter of 2023, the stock was composed in aggregate of 6% cash, 27% Level 1 assets, 13% Level 2A 
assets, and 54% Level 2B assets. 

44    HQLA excluding cash may be (i) used to meet the part of a margin call pertaining to higher initial margin 

requirements, (ii) pledged as collateral in the repo market to source additional cash, or (iii) sold. 

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Chart B 
Euro area investment funds can rely on high levels of HQLA holdings to meet margin calls, but these 
assets may become illiquid in periods of stress 

a) Ratio of initial margins posted to HQLA 

b) Ratio of margin flows (initial and variation) to 
HQLA 

(Feb.-Apr. 2020, Q1 2022-Q4 2023; percentages) 

(Feb.-Apr. 2020, Q1 2022-Q4 2023; percentages) 

Sources: ECB (EMIR, CSDB), EMIR sector enrichment based on Lenoci and Letizia*, LSEG Lipper and ECB calculations. 
Notes: The HQLA stock at fund level is calculated in line with the methodology set out in a previous issue of the Financial Stability Review**; it comprises cash, 
Level 1, Level 2A and Level 2B holdings. “Pandemic” refers to the period between February and April 2020. The whiskers refer to the 15th and 85th percentiles. 
For confidentiality reasons, the percentiles of the distribution are calculated by averaging values across four entities. Panel a: the chart shows the distribution of 
the maximum over the quarter of the ratio of the stock of initial margin posted divided by the HQLA stock as of end of the month, at fund level. Panel b: margins 
flows are calculated as the weekly (from Wednesday to Wednesday) difference between the stock of margins defined as the sum of initial and variation margins 
posted minus variation margins received (therefore outflows have a positive sign). Therefore, margin flows might, by design, suffer from distortions around the 
contract closure, when the stock of related variation margin posted is reset to zero, without a corresponding exchange of cash. The ratio is calculated by first 
dividing the maximum weekly flows over the month by the HQLA stock as of the previous month, at fund level, and then taking its maximum over the quarter. 
HQLA holdings posted to meet margin requirements are reflected in both the numerator and the denominator of the ratios. 
*) See Lenoci, F.D. and Letizia, E., op. cit. 
**) See the box entitled “Assessing liquidity vulnerabilities in open-ended bond funds: a fund-level redemption coverage ratio approach”, Financial Stability 
Review, ECB, November 2023. 

The new indicators of funds’ liquidity preparedness for margin calls reveal some 
vulnerabilities in the fund sector that could lead to procyclical behaviours and amplify 
market-wide stress. A “dash for cash” driven by large margin calls could lead to asset fire sales or a 
rapid unwinding of derivative exposures, which might further fuel already high price volatility and lead 
to disorderly market functioning. In the event of extraordinarily large market moves, the failure of 
funds to meet margin calls could spread to other market participants, such as banks acting as clearing 
members of central counterparties or dealers in the bilaterally cleared OTC space. This suggests that 
it is important to ensure that adequate cash buffers and diverse and reliable sources of liquidity and 
collateral are in place. The indicators proposed in this box are valuable monitoring tools for 
strengthening the governance and liquidity risk management of investment funds, enhancing 
contingency planning and governance, and performing liquidity stress tests. 

4.3 

Strong solvency but uncertain profitability outlook for 
insurers 

Euro area insurance corporations remain resilient overall, although profitability 
challenges remain, especially for life insurers. Insurers’ Solvency Capital 
Requirement (SCR) coverage ratios remained well above the regulatory minimum of 

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100% and increased marginally in 2023 (Chart 4.6, panel a).45  However, the 
profitability outlook remains less certain. Life insurers saw the ratio of premiums 
written to claims incurred and acquisition expenses decline slightly in 2023, as claims 
increased relative to previous years (Chart 4.6, panel b). Limited growth in demand for 
new policies is most likely attributable to worsening real household incomes and the 
availability of higher returns from other asset classes.46  However, positive 
macroeconomic outcomes and increasing returns on life insurance products could 
support growth in underwriting going forward. 

Chart 4.6 
Insurers’ solvency remains strong, but life insurers’ underwriting profitability has fallen 

a) SCR ratios of large euro area insurance 
groups 

b) Euro area life insurers’ ratio of premiums to 
claims and expenses 

(Q1 2021-Q3 2023, percentages) 

(Q1 2021-Q3 2023; € billions, percentages) 

Sources: ECB (LIG) and ECB calculations. 
Notes: Panel a: the SCR coverage ratio is defined as eligible own funds divided by SCR. Panel b: the ratio is cumulative over the period 
Q1 to Q4 of each year for large euro area insurance groups’ life business. 

The period of ultra-low interest rates coming to an end may help ICPFs become 
more resilient in the medium term, although it is still important for them to 
strengthen their liquidity preparedness. Insurance corporations and pension funds 
(ICPFs) generally benefit from higher interest rates, given their negative duration 
gaps.47  Additionally, rising rates may also increase their demand for higher-quality 
bonds, which may help to lower credit risk. At the same time, any sharp increase in 
financial market volatility or interest rates could expose those ICPFs that use interest 
rate derivatives to large margin calls. Recent stress events, such as the March 2020 
market turmoil and the UK gilt market episode, demonstrate how liquidity pressures 

45    Note that where insurers employ transitional measures, the reported SCR ratio does not account for 

potential unrealised losses in their asset portfolios. For further discussion, see the “Report on Long-Term 
Guarantee Measures and Equity Risk 2020”, EIOPA, December 2020. 

46    See “Financial Stability Report – December 2023”, EIOPA, 11 December 2023. 
47    The duration gap refers to the difference between the duration (average maturity) of assets and liabilities. 
When the duration of assets is larger (smaller) than that of liabilities, the insurer has a positive (negative) 
duration gap. Insurers and pension funds typically have a negative duration gap, implying that they 
benefit from rising interest rates, whereas banks have a positive duration gap. 

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faced by ICPFs can propagate stress across the wider financial system. This 
underscores how important it is for ICPFs to strengthen their liquidity preparedness to 
meet margin calls (Chapter 5). 

Additionally, insurers have seen their investment income remain relatively 
unchanged despite higher interest rates. Income from bond investments increased 
marginally in 2023, whereas the annual yield on insurers’ bond portfolios remained at 
around 2% (Chart 4.7, panel a). This reflects the insurers’ large share of long-dated 
bond holdings acquired during a period of ultra-low interest rates and the prevalence 
of fixed-rate coupons (Section 4.1). In the short term, any fall in interest rates could 
further depress investment income. In the longer term, however, insurers are still likely 
to benefit from improved returns as they gradually roll over their portfolios at higher 
yields than in the past. Additionally, ICPFs have increased their allocation to 
alternative, typically higher-yielding assets, such as private equity, private credit and 
real estate. These may improve investment returns while also posing risks (Special 
Feature C). 

Chart 4.7 
Euro area insurers are exposed to falling investment income and corrections in 
commercial real estate markets 

a) Euro area insurers’ investment income on 
bond holdings, by maturity bucket 

b) Euro area ICPF real estate exposures, by 
type 

(Q1 2021-Q4 2023; € billions, percentages) 

(Q3 2023; € billions, percentages of total real estate exposures) 

Sources: ECB (SHS), EIOPA and ECB calculations. 
Notes: Panel a: the chart shows the investment income for bond holdings only, broken down by maturity bucket. Panel b: REIF stands for 
real estate investment fund. 

Insurers may face revaluation losses on real estate investments, which could 
weigh on profitability. During the period of ultra-low interest rates that prevailed until 
2022, ICPFs significantly increased their holdings of less liquid assets, especially real 
estate.48  This mainly reflects indirect investment in euro area real estate through REIF 
shares, other equities and debt securities (Chart 4.7, panel b). The ongoing correction 

48    See chapter 4.3 in the “Financial Stability Review – May 2023”, ECB, May 2023. 

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in commercial real estate markets (Chapter 1) could result in losses on these 
exposures, which would weigh on insurers’ profitability. Further corrections could 
increase redemption pressures and the potential for forced sales by open-ended 
REIFs (Section 4.2), with potential losses for their investors, including ICPFs. 
Consequently, interconnectedness in commercial real estate exposures across the 
financial system warrants continued monitoring. 

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5 

Macroprudential policy issues 

5.1 

Preserve banking sector resilience and enhance the 
macroprudential framework for banks 

In recent years, the euro area banking sector has proven its resilience during a 
series of adverse shocks, thanks in part to decisive and comprehensive 
macroprudential action. Since the pandemic, rising capital buffers have further 
boosted the banking sector’s resilience to shocks and have helped to create additional 
macroprudential space.49  They have complemented the existing borrower-based 
measures that have been effective in bolstering borrowers’ resilience, as 
demonstrated by the limited deterioration in mortgage credit quality seen so far. 

Maintaining existing macroprudential buffer requirements remains a priority, 
with a view to ensuring that banks are resilient to potential headwinds. 
Notwithstanding the tentative improvements seen in the financial stability outlook, 
global macroeconomic prospects are surrounded by a high level of uncertainty and tail 
risks remain (Chapter 1). Moreover, asset quality is slowly deteriorating, with 
commercial real estate and low provisioning levels of most concern (Chapter 3). In 
this context, and in the absence of signs of widespread losses and credit supply 
constraints arising from bank capital, it is advisable to maintain existing capital buffer 
requirements in case they are needed in the event of a deterioration in banking sector 
or macro-financial conditions. Borrower-based measures should continue to fulfil their 

49    Since the November 2023 issue of the Financial Stability Review was published, two macroprudential 
authorities have introduced a positive neutral rate for the countercyclical capital buffer (CCyB). At 
present, seven of the 14 banking union countries with a positive CCyB rate have implemented a positive 
neutral CCyB rate (Estonia, Ireland, Cyprus, Latvia, Lithuania, the Netherlands and Slovenia). 11 
countries have a sectoral systemic risk buffer (SyRB) in place to address emerging broad or 
sector-specific vulnerabilities, while borrower-based measures are active in 16 countries. 

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role as structural backstops and should be maintained to ensure that lending 
standards remain sound.50  Furthermore, the ECB has continued to highlight its 
concerns over the implications of initiatives to impose extraordinary taxes on credit 
institutions in the interests of financial stability.51  Not only may such diverse, ad hoc 
fiscal actions create uncertainty for banks and their investors, they may also make it 
harder for banks to build up further capital buffers at a time when ensuring a sound 
capital base is essential. 

Over the medium term, further enhancing macroprudential space through 
releasable buffers is a robust policy strategy for enhancing the resilience of the 
banking sector. Since the pandemic, authorities in the banking union have increased 
the amount of releasable buffers through more active use of the countercyclical capital 
buffer (with several authorities activating a positive neutral rate for this buffer) or the 
systemic risk buffer. By increasing the macroprudential space available to support the 
banking sector in the event of (potentially severe) shocks that could occur at any 
phase of the cycle, a higher amount of releasable capital buffers enables 
macroprudential authorities to act countercyclically in a more effective manner (Chart 
5.1, panel a). More widespread use of releasable buffers has resulted in a noticeable 
increase in macroprudential space, with the total amount of releasable buffers in the 
banking union reaching around €82 billion,52  although some jurisdictions do not have 
any releasable buffers in place. Where favourable conditions limit the likelihood of 
procyclical effects, it is therefore desirable to broaden macroprudential space still 
further, for example through the implementation of a positive neutral rate for the 
countercyclical capital buffer. The economic cost of recent increases in the buffer 
requirements has been low because of banks’ existing capital headroom and robust 
profitability (Chart 5.1, panel b).53 

50    At the same time, targeted adjustments to design elements of borrower-based measures, as recently 
applied by some euro area authorities, help to avoid excessive procyclicality in mortgage supply and 
preserve access to credit for specific segments of borrowers. 

51    See the Financial Stability Review, ECB, November 2023, the Opinion of the European Central Bank of 
11 December 2023 on a temporary mortgage loan borrower protection fee payable by credit institutions 
(CON/2023/42), the Opinion of the European Central Bank of 15 December 2023 on the imposition of a 
tax on credit institutions (CON/2023/45) and the Opinion of the European Central Bank of 14 February 
2024 on a special levy for credit institutions (CON/2024/4). 

52    The figure refers to all releasable buffers announced by national authorities as of the fourth quarter of 
2023. A more proactive use of the CCyB in the banking union resulted in an increase in the weighted 
average CCyB rate from 0.23% at the onset of the pandemic to 0.5% in the fourth quarter of 2023. 
53    See Chart 5.1, panel a) in the chapter entitled “Macroprudential policy issues”, Financial Stability Review, 

ECB, November 2023. 

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Chart 5.1 
Macroprudential space enhances the effectiveness of countercyclical macroprudential 
action while favourable banking sector conditions mitigate the economic costs of 
increasing capital requirements 

a) Impulse responses of GDP to a 
recessionary shock for different levels of 
releasable capital buffers available 

b) Impact on credit growth of a 1 percentage 
point increase in the combined buffer 
requirement for different levels of capital 
headroom 

(x-axis: quarters after shock; y-axis: percentage deviations from 
the steady state) 

(x-axis: capital headroom as a percentage of risk-weighted assets; 
y-axis: credit growth in percentage points) 

Sources: ECB (AnaCredit, supervisory data), ECB calculations and national notifications. 
Notes: Panel a: a higher share of releasable buffers provides macroprudential authorities with greater leeway to respond to severe 
shocks. Simulations were performed using the 3D DSGE model calibrated for the euro area*. The chart shows the impulse responses of 
GDP to a mix of negative housing and physical capital price shocks triggering a (peak) -1.5 percentage point decline in GDP in the 
baseline scenario with no releasable capital buffers (red line). The yellow line depicts the GDP response when the macroprudential 
authorities fully release the available 1% capital buffer, while the blue line represents the GDP response when the macroprudential 
authorities fully release the available 2% capital buffer. The exercise assumes that (i) capital buffers are fully usable and are not 
constrained by other parallel requirements; and (ii) banks fully use the released buffer, decreasing their capital ratios in line with the 
amount of the release. Panel b: higher capital headroom limits the cost of capital buffer increases. The chart shows the impact on credit 
growth of a 1 percentage point increase in the combined buffer requirement (CBR) for different levels of capital headroom (defined as the 
distance to the CBR) based on bank-firm level panel regressions using a sample of almost 15 million observations for 2,088 euro area 
banks (significant institutions and less significant institutions) over the period from Q2 2021 to Q2 2023. The econometric model also 
includes a set of bank-level controls, bank fixed effects and firm-quarter dummies. The red lines indicate the 90% confidence intervals 
around the point estimate. The blue diamond represents the impact on credit growth for banks above the first quintile of the capital 
headroom distribution, while the yellow diamond represents the impact on credit growth for banks below the first quintile of the capital 
headroom distribution. The red diamond represents the estimated differential impact between banks with capital headroom below the 1st 
quintile of the capital headroom distribution (3.6%) and those with capital headroom above 3.6%. Confidence intervals overlapping at 
zero indicate that the effect on credit growth is not statistically significant. 
*) See Mendicino, C., Nikolov, K., Suarez, J. and Supera, D., “Bank capital in the short and in the long run”, Journal of Monetary 
Economics, Vol. 115, November 2020, pp. 64-69. 

In this context, further progress on regulatory initiatives aimed at improving the 
efficiency and effectiveness of the EU macroprudential framework remains a 
priority. The ECB welcomes the European Commission’s report on the review of the 
EU macroprudential framework and strongly supports proposals aimed at enhancing 
the effectiveness and consistency of the macroprudential toolkit, simplifying 
macroprudential coordination mechanisms and broadening macroprudential space.54 
In this regard, promoting the build-up of releasable buffers, including through a more 
flexible use of the countercyclical capital buffer, and enhancing their usability are of 
key importance. While the full applicability of final targets for minimum requirements 
for own funds and eligible liabilities (MREL) as of 2024 will significantly improve the 

54    See the “ECB response to the European Commission’s call for advice on the review of the EU 

macroprudential framework”, ECB, March 2022. 

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resolvability of EU banks, it is important to assess the resulting implications for capital 
buffer usability arising from parallel capital requirements.55  This will warrant enhanced 
information-sharing between macroprudential and resolution authorities on MREL 
targets.56  The ECB also reiterates its call for a more consistent use of macroprudential 
instruments across jurisdictions, particularly of the sectoral SyRB, to promote the 
coherent treatment of systemic risks across countries. 

Recent initiatives by the Basel Committee and the implementation of the final 
Basel III reforms in the EU will further enhance the effectiveness of 
macroprudential policy and contribute to financial stability. In April 2024 the 
Basel Committee published its revised Basel Core Principles for Effective Banking 
Supervision, emphasising the importance of close cooperation between supervisory 
and macroprudential authorities and reflecting regulatory and supervisory 
developments since the last revision.57  In the EU, the final Basel III reforms are being 
introduced via the EU banking package, which is currently being adopted by the 
European Parliament and the EU Council. The reforms will become effective on 1 
January 2025 and will further bolster the resilience of the EU banking system, 
enhance the supervisory toolkit and address climate-related and other sustainability 
risks. 

5.2 

Progress towards a capital markets union requires a solid 
institutional and policy framework for non-banks 

Non-banks play a pivotal role in the development of capital markets but, unlike 
banks, they largely lack a macroprudential framework. As the euro area non-bank 
financial intermediation (NBFI) sector has grown considerably in size since the global 
financial crisis, it has become an increasingly important source of funding for the real 
economy.58  By reducing reliance on bank-based financing, this expansion has helped 
to diversify the sources of financing and contributed to the development of capital 
markets. However, parts of the NBFI sector exhibit significant vulnerabilities 
(Chapter 4), and the institutional and policy framework largely lacks a 
macroprudential perspective. 

Enhancing the macroprudential framework for non-banks could help ensure 
that they provide a stable source of financing through the financial cycle – a key 
feature for building a strong capital markets union. But there is more work to be 
done to achieve this goal, as illustrated by several periods of stress in recent years. 

55    See, for instance, “Report of the Analytical Task Force on the overlap between capital buffers and 

minimum requirements”, European Systemic Risk Board, December 2021, and Leitner, G. et al., “How 
usable are capital buffers?”, Occasional Paper Series, No 329, ECB, 2023. 

56    At the same time, other factors will also affect and improve buffer usability. For example, the entry into 
force of the final Basel III rules, the expiration of both TLTRO III and public guarantees for non-financial 
corporation loans will increase banks’ risk density and reduce the overlap between minimum 
requirements and buffers. 

57    These principles, first adopted in 1997, set global standards for the sound prudential regulation and 

supervision of banks. They were previously revised in 2012. 

58    See the box entitled “Measuring market-based and non-bank financing of non-financial corporations in 

the euro area”, Financial Integration and Structure in the Euro Area, ECB, April 2022. 

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For example, the March 2020 market turmoil and the UK government bond (gilt) 
market stress in 2022 brought to the fore structural vulnerabilities in non-banks, such 
as excessive leverage, inadequate liquidity preparedness, liquidity mismatches and 
interconnectedness.59  Against this background, the ECB welcomes the European 
Commission’s plan for a targeted consultation on macroprudential policies for the 
NBFI sector in 2024.60 

A comprehensive macroprudential framework for non-banks should be based 
on several key principles. First, a system-wide perspective is needed to address the 
vulnerabilities in the NBFI sector holistically. This involves taking into consideration 
interdependencies between non-banks and linkages with the banking sector and the 
real economy. In the March 2020 market turmoil, for instance, forced asset sales by 
non-banks amplified the adverse market dynamics and liquidity risk spilled over to 
short-term debt securities issued by banks and firms through money market funds 
(MMFs).61  Second, a macroprudential framework should also focus on building up 
resilience ex ante rather than relying on ex post measures. This would help to prevent 
stress from emerging in non-banks so as to ensure that, even in times of market 
stress, they can provide a resilient source of funding. Finally, given the varied nature of 
the NBFI sector, the macroprudential framework should allow for policies to be tailored 
to the diverse set of entities and activities involved. 

In this regard, the Financial Stability Board (FSB) has issued recommendations 
that are crucial for the EU to implement. Implementing these regulations would 
increase resilience and foster a level playing field across the NBFI sector, both within 
the EU and globally. The level playing field is needed to mitigate the risk of 
cross-border fragmentation, regulatory arbitrage and/or business reallocation, as well 
as risks stemming from globally interconnected entities and activities. 

The first concern is reform of MMFs. Overall, the progress made in implementing 
the international standards for MMFs developed in response to the March 2020 
market turmoil has been uneven across jurisdictions.62  Authorities in the United States 
recently raised the liquidity requirements for MMFs, requiring them to hold weekly 
liquid assets of at least 50% of a fund’s total assets.63  In the United Kingdom, the 
authorities recently proposed the same requirements in a public consultation. By 
contrast, in the euro area these requirements range from 15% to 30%, depending on 

59    See the box entitled “Non-banks’ liquidity preparedness and leverage: insights and policy implications 

from recent stress events”, Financial Stability Review, ECB, May 2023. 

60    See the European Commission’s report on the review of the EU macroprudential framework. 
61    See, for example, the section entitled “Forced asset sales by non-banks amplified market dynamics” and 
the box entitled “Recent stress in money market funds has exposed potential risks for the wider financial 
system”, Financial Stability Review, ECB, May 2020, and the box entitled “Interconnectedness of 
derivatives markets and money market funds through insurance corporations and pension funds”, 
Financial Stability Review, ECB, November 2020. 

62    At the international level, see “Policy Proposals to Enhance Money Market Fund Resilience: Final 
Report”, FSB, October 2021. At the European level, see “Eurosystem contribution to the European 
Securities and Markets Authority (ESMA) consultation on the framework for EU money market funds”, 
ECB, June 2021; “Recommendation of the European Systemic Risk Board of 2 December 2021 on 
reform of money market funds”, ESRB, January 2022; and “ESMA opinion on the review of the Money 
Market Fund Regulation”, Final Report, ESMA, February 2022. 

63    On 12 July 2023 the US Securities and Exchange Commission adopted amendments to certain rules that 

govern MMFs. 

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fund type. This leaves MMFs domiciled in the euro area less resilient to liquidity 
shocks in comparison. Moreover, for euro area MMFs which invest in assets 
denominated in foreign currencies (e.g. GBP-denominated MMFs domiciled in 
Ireland), rules that diverge globally can create opportunities for regulatory arbitrage, 
while weaker resilience could also trigger spillovers to funding markets in jurisdictions 
outside the euro area.64,65 

Second, the FSB recently published its revised recommendations on liquidity 
mismatch in open-ended funds (OEFs).66  These recommendations aim to better 
align fund redemption terms with the liquidity of a fund’s asset portfolio and to enhance 
the availability and use of liquidity management tools. This would enable OEFs to pass 
on to redeeming investors the explicit and implicit costs of selling assets under both 
normal and stressed market conditions.67  It should, in turn, reduce first-mover 
advantage and disincentivise procyclical investor redemptions. 

Implementation of the FSB’s recommendations for OEFs should continue in the 
EU, and the effectiveness of the reforms should be assessed in due course. In 
the EU, amendments to the regulatory frameworks for funds were published in 
November 2023 and are expected to enter into force in the first quarter of 2026.68 
Among other things, this new legislation aims to promote greater availability and use 
of liquidity management tools, including the suspension of redemptions, redemption 
gates, the extension of notice periods, redemption fees, swing pricing, dual pricing, 
anti-dilution levies, redemptions in kind and side pockets. Going forward, the extent to 
which these reforms will be effective in reducing vulnerabilities arising from liquidity 
mismatch in OEFs remains to be seen. It should also be borne in mind that the 
European Securities and Markets Authority (ESMA) is still in the process of developing 
more detailed standards on the implementation of these liquidity management tools. 

The FSB is also working on recommendations which would enhance liquidity 
preparedness across the NBFI sector to meet margin and collateral calls. 
Specifically, it recently published a consultation paper proposing eight policy 
recommendations. These cover non-banks’ liquidity risk management and 
governance, their stress testing and scenario design, and their collateral management 
practices, all of which aim to mitigate liquidity risks arising from spikes in margin and 
collateral calls.69  The FSB’s recommendations apply to a wide range of non-banks 
and cover both centrally and non-centrally cleared derivatives and securities markets. 

64 The FSB recently recommended that “FSB jurisdictions that have not yet done so should review their 

policy frameworks and adopt tools to address identified MMF vulnerabilities, taking into consideration the 
2021 FSB policy proposals. […] including by taking account of experience with previous stress events, 
potential cross-border spillovers and regulatory arbitrage.” See “Thematic Review on Money Market 
Fund Reforms: Peer review report”, FSB, February 2024. 

65 See also the discussion in Box 6 of this issue of the Financial Stability Review on measures targeted at 
GBP-denominated liability-driven investment funds domiciled in Ireland, Luxembourg and the United 
Kingdom. 

66 See “Revised Policy Recommendations to Address Structural Vulnerabilities from Liquidity Mismatch in 

Open-Ended Funds”, FSB, December 2023. 

67 See also IOSCO’s guidance on anti-dilution liquidity management tools. 
68 These are amendments to the Alternative Investment Fund Managers Directive (AIFMD) and the 
Undertakings for Collective Investment in Transferable Securities Directive (UCITS Directive). 
69 See “Liquidity Preparedness for Margin and Collateral Calls: Consultation report”, FSB, April 2024. 

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Because of the important interlinkages between liquidity preparedness and 
transparency, the recommendations are being developed at the same time as other 
international recommendations for good margining practices in centrally and 
non-centrally cleared markets.70  For instance, if central counterparties were required 
to provide margin simulation tools to clearing members and clients (typically 
non-banks), this could provide significant support to non-banks carrying out liquidity 
stress tests. 

Once finalised, the recommendations on margin and collateral calls should be 
swiftly implemented in the EU across a wide range of non-banks. Box 5 
suggests that over 15% of euro area OEFs and exchange-traded funds do not appear 
to be adequately prepared to cope with potential spikes in margin calls. Based on 
previous studies, this is the case not only for euro area investment funds but also for 
some insurers and pension funds, where the latter might be able to meet margin calls 
but only if money markets are functioning properly.71  In view of this vulnerability, it is 
vital for the forthcoming recommendations to be implemented swiftly in the EU in both 
entity-level regulations (e.g. AIFMD, UCITS, Solvency II and IORP II Directives) and 
activity-based regulations (e.g. EMIR and SFTR), including through the ongoing EU 
reforms.72 

The FSB is currently also exploring policies which aim to address the risks 
arising from NBFI leverage, including ways to contain its build-up.73  Given the 
complexities involved in using leverage in an interconnected financial system, 
leverage-related risks should be tackled from several angles, ensuring that measures 
can be targeted to specific types of entities or activities. Table 5.1 provides an 
overview of the different policy measures that can contain the build-up of leverage as 
well as key considerations for assessing their potential effectiveness and costs. These 
include (i) activity-based measures (e.g. haircuts/margins and clearing mandates), (ii) 
entity-based measures (e.g. leverage limits), (iii) supervisory and regulatory guidance 
on leverage providers (e.g. risk management practices), and (iv) enhanced 
transparency (e.g. disclosures to counterparties and/or market participants to foster 
market discipline). Measures that can contain the build-up of leverage can do so 
directly (e.g. entity-level leverage limits) or indirectly (e.g. rules on leverage providers), 
and can also do so when they have different primary objectives (e.g. mitigating the 
probability of procyclical deleveraging or counterparty losses). 

70    See the BCBS-IOSCO report “Streamlining VM processes and IM responsiveness of margin models in 

non-centrally cleared markets”, Bank for International Settlements, January 2024; the 
BCBS-CPMI-IOSCO report “Transparency and responsiveness of initial margin in centrally cleared 
markets – review and policy proposals”, Bank for International Settlements, January 2024; and the 
CPMI-IOSCO report “Streamlining variation margin in centrally cleared markets – examples of effective 
practices”, Bank for International Settlements, January 2024. 

71    See “Impact of variation margining on EU insurers’ liquidity: an analysis of interest rate swaps positions”, 

2019 Thematic Review, EIOPA, January 2023; the special feature entitled “Derivatives-related liquidity 
risk facing investment funds”, Financial Stability Review, ECB, May 2020 (especially the box entitled 
“Liquidity stress simulations of euro area pension funds’ interest rate swap portfolios”); the box entitled 
“Interconnectedness of derivatives markets and money market funds through insurance corporations and 
pension funds”, Financial Stability Review, ECB, November 2020; and the joint DNB-AFM study 
“Liquidity risks of pension funds’ derivatives portfolios under various stress scenarios”, De 
Nederlandsche Bank, February 2024. 

72    IORP stands for institutions for occupational retirement provision, EMIR for the European Market 

Infrastructure Regulation and SFTR for Securities Financing Transactions Regulation. 

73    See “FSB Work Programme for 2024”, FSB, January 2024. 

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Table 5.1 
Policy options for containing the build-up of NBFI leverage and key considerations 

Type of policy 
measure 

Activity-based 
(e.g. haircuts/ 
margins, clearing 
mandate) 

Description 

Key considerations 

Initial margin for derivatives determines the 
amount of exposure that can be created. 

Activity-based measures can act as a backstop for entities not 
subject to direct leverage constraints. 

Haircuts for repos determine the amount of 
funding that can be obtained for a given 
amount of collateral. 

Clearing mandate may contain the build-up of 
risk exposures via stricter risk management 
and requirements on collateral. 

Margins/haircuts help to reduce the level of leverage in 
aggregate but are less effective against the build-up of 
concentrated positions. May be costly for non-leveraged 
users. 

Clearing mandates already exist for key derivative classes but 
would not be suitable for others, especially those which are 
less liquid. 

Entity-based (e.g. 
leverage limits) 

Simple limits impose a direct constraint on the 
amount of leverage a fund is able to take on. 

Risk-based limits, usually informed by risk 
metrics (e.g. VaR) or stress testing, ensure that 
funds maintain a certain level of resilience. 

Leverage limits can effectively target the build-up of leverage 
in specific entities/sectors and activities, especially for highly 
leveraged funds and concentrated positions. 

Effective stress-testing practices can be helpful in informing 
the calibration of limits and the appropriate level of resilience. 

The measurement and calibration of leverage limits may be 
more difficult for funds employing complex strategies. 

Leverage 
providers (e.g. 
risk management 
practices) 

Rules on counterparty credit risk 
management for banks/prime brokers can 
reduce the level of leverage by promoting more 
prudent provision of leverage to NBFI 
counterparties. 

Offers a complementary angle for mitigating the build-up of 
leverage in the NBFI sector globally, especially for entities that 
are not subject to regulatory leverage constraints. 

The focus is usually microprudential to mitigate counterparty 
risk and may therefore lack a systemic dimension. 

Transparency 
(e.g. disclosures) 

Disclosures can help ensure that 
investors/counterparties are better informed of 
risks – especially concentrated positions – and 
may contain leverage via enhanced market 
discipline. 

Depends also on having adequate information. 

Requires market participants or counterparties to use 
information to price risks adequately. 

Can support market discipline of entities/activities that lie 
outside the regulatory perimeter or are subject to less stringent 
rules. 

Can be an important complement to other policies but on its 
own is unlikely to have to a material impact on containing the 
build-up of NBFI leverage. 

Authorities need to carefully balance key trade-offs when designing policy 
measures – their effectiveness, feasibility and potential costs. A wide range of 
policy measures are used by authorities across the globe to address leverage-related 
risks (Box 6). The choice of measure requires careful consideration of the given 
circumstances, as these affect how suitable a tool is for targeting specific risks. At the 
same time, authorities may face significant constraints, including the scope of their 
financial stability mandates and the complexity involved in calibrating the measures. 
Moreover, it is important to ensure that the resulting actions do not impose 
disproportionate costs, such as those associated with negatively affecting liquidity and 
pricing in underlying markets or hedging incentives. To cite one example, while 
entity-based measures (e.g. leverage limits) can be effective in targeting leverage 
directly, their use may not always be feasible as entities may lie outside the regulatory 
perimeter (e.g. family offices), for instance, or engage in highly complex investments 
(e.g. multi-strategy hedge funds). In such cases activity-based measures (e.g. 
haircut/margin requirements or clearing mandates) may be an important complement. 
However, haircuts and margins may be less effective in targeting the build-up of 
concentrated positions and, if set too strictly, could impose excessive costs on 
hedging for end users. 

In addition to developing macroprudential tools, more deeply integrated 
EU-wide supervision of non-banks would help to mitigate financial stability 

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risks across the EU. European supervisory authorities are already helping to 
promote supervisory convergence to non-banks across the EU. There is, however, a 
case for enhancing the supervisory architecture of EU capital markets to reflect the 
growing importance of the cross-border activities of the NBFI sector. This would 
ensure that it remains resilient under stress and does not amplify systemic risk or 
generate cross-border contagion. A more integrated supervisory framework would 
also promote the EU level playing field and reduce the potential for regulatory 
arbitrage. It is therefore essential to ensure that the European supervisory authorities 
(especially ESMA and EIOPA) have independent, European governance, sufficient 
resources and comprehensive oversight powers. They should directly supervise the 
most systemic cross-border capital market actors, in cooperation with their national 
supervisors.74  In addition, the availability of data to all European and national 
authorities with a financial stability mandate, including central banks, should be 
enhanced through greater data sharing and/or direct access to these data. 

A resilient NBFI sector would help to promote and complement the objectives 
of the capital markets union. Policies supporting the resilience of the NBFI sector 
are key to safeguarding Europe’s financial stability. Furthermore, deep, integrated 
capital markets are essential to mobilise the kind of private risk-sharing that would 
help to enhance economic growth and smooth out asymmetric shocks. Making full use 
of Europe’s capital markets is also key to mobilising private investment in the green 
and digital transitions needed to enhance the EU’s productivity and competitiveness in 
a challenging geopolitical landscape. 

In addition to policies safeguarding the stability of the NBFI sector, the capital 
markets agenda would benefit from policies supporting the efficiency and 
liquidity of equity markets. European firms would gain from deeper and more 
integrated capital markets, which would allow them to access a large and diversified 
pool of equity finance in the EU. The current fragmentation of the EU stock exchange 
landscape is a concern as it constrains stock market efficiency and initial public 
offering activity. In addition to the measures taken in recent years to reduce the 
regulatory cost of listing for smaller companies, the market would also benefit from 
initiatives supporting large EU-based institutional investors such as asset managers 
and pension funds. It would also gain from a better integrated trading and post-trading 
infrastructure, which could be achieved by harmonising listing requirements and 
consolidating stock exchanges and market infrastructures. 

Finally, securitisation could play a role in financing the real economy by 
transferring risks from banks to non-banks and by providing a source of 
funding to non-banks. Securitisation could be part of a diversified funding mix for 
banks and non-banks alike. Banks could use it as a tool to free up their balance 
sheets, thereby creating room for lending to the real economy. This is particularly 
important in view of the investment needed for the green and digital transitions. From a 
financial stability perspective, policy measures in the regulatory framework should aim 
to ensure that the market develops prudently and sustainably and should lead to 

74  See also the “Statement by the ECB Governing Council on advancing the Capital Markets Union”, ECB, 

7 March 2024. 

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genuine risk transfer. This would ensure that risks are distributed across the financial 
sector to those best placed to assume them. Public guarantees and further 
standardisation through pan-EU issuances could support targeted segments of 
securitisation, such as specific securitisation to support the green transition. Because 
securitisations are currently concentrated in a limited number of countries, further 
standardisation could widen the investor base and facilitate the development of the 
market across the EU. 

5.3 

Other ongoing policy initiatives that support euro area 
financial stability 

Topic 

Crypto-assets 

Digital euro 

Implementation of the regulatory framework for crypto-assets in the EU, the Markets in Crypto-assets (MiCA) 
Regulation, is progressing.75  The European Banking Authority and the European Securities and Markets Authority 
are finalising a large number of technical standards to implement the regulation. At the same time, the European 
Commission has adopted a number of associated delegated and implementing acts. The most relevant of these for 
financial stability specifies the criteria for classifying asset-referenced tokens and e-money tokens as significant, 
which would make them subject to stricter prudential requirements and heightened supervision, given their higher 
financial stability risks. At the international level, the Financial Stability Board (FSB) is focusing on the 
implementation of its high-level recommendations for regulating crypto-asset activities and markets as well as global 
stablecoin arrangements in FSB jurisdictions. It is, however, also trying to capture non-FSB jurisdictions. In 
December 2023 the Basel Committee on Banking Supervision published a consultation aimed at clarifying aspects 
of its standard on banks’ exposures to crypto-assets and tightening the criteria that stablecoins need to satisfy to 
receive preferential regulatory treatment. While it is important for the full Basel standard on crypto-assets to be 
implemented in the EU in a timely manner, the finalisation of the amended Capital Requirements Regulation already 
includes a welcome transitional treatment of banks’ crypto-asset exposures, including disclosure requirements. 

Following the requests for opinions from the European Council and the European Parliament in September 2023, in 
October the ECB published its Opinion on the digital euro. The legal framework for the digital euro is key to ensuring 
that central bank money remains widely accessible and is accepted throughout the euro area in an increasingly 
digitalised economy. The ECB remains committed to contributing to the ongoing debate on the digital euro project 
and to liaising closely with European institutions and authorities. 

The initial preparation phase of the digital euro project started in November 2023 and will last two years. After that, 
the ECB’s Governing Council will decide whether to move on to the next preparation stage, paving the way for the 
possible future issuance and roll-out of a digital euro. 

Climate 

Crisis 
management 
and deposit 
insurance 

In December 2023 the ECB and the European Systemic Risk Board (ESRB) published a joint report entitled 
“Towards macroprudential frameworks for managing climate risk” that presents policy options for addressing climate 
risks in the banking sector. The report sets out options encompassing the use of the systemic risk buffer, 
concentration measures and targeted adjustments to borrower-based measures, alongside initiatives aimed at 
reducing the insurance protection gap and addressing information failures in non-bank financial intermediation. 

In July 2023 the ECB published its Opinion on the European Commission’s proposal to reform the EU’s crisis 
management and deposit insurance (CMDI) framework and called for improved options for handling failures of 
mid-sized and smaller banks. This would be achieved by broadening the scope of resolution, enhancing the tools 
available in national liquidation frameworks and empowering deposit guarantee schemes to intervene in bank crisis 
management in ways that are more effective than a payout for covered depositors. Since then, the European 
Council and the European Parliament have made progress on establishing their negotiation positions, and the ECB 
is encouraging legislators to conclude the CMDI reform as a matter of priority following the elections to the European 
Parliament in June 2024. This would at least maintain momentum on completing the banking union. 

75    Regulation (EU) 2023/1114 of the European Parliament and of the Council of 31 May 2023 on markets in 
crypto-assets, and amending Regulations (EU) No 1093/2010 and (EU) No 1095/2010 and Directives 
2013/36/EU and (EU) 2019/1937 (OJ L 150, 9.6.2023, p.40). 

Financial Stability Review, May 2024 – Macroprudential policy issues 

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Box 6 
Containing risks from leverage in the NBFI sector – insights from recent policy initiatives 

Prepared by Michael Grill, Luis Molestina Vivar, Charles O’Donnell and Christian Weistroffer 

Recent stress episodes have shown how leverage in the non-bank financial intermediation 
(NBFI) sector can be a source of systemic risk and amplify stress in the wider financial 
system. Excessive leverage in the NBFI sector can increase the likelihood of procyclical 
deleveraging and counterparty losses, with potential spillovers to banks and the broader financial 
system. Prominent examples of procyclical deleveraging include the role of leveraged hedge funds in 
the US Treasury market in March 2020 and liability-driven investment (LDI) funds in UK gilt markets in 
September 2022.76  Both reveal how NBFI vulnerabilities associated with high leverage can spill over 
to core government bond markets. The failure of Archegos Capital Management in March 2021 
highlights how the build-up of concentrated derivative positions combined with a lack of transparency 
on these positions can impose significant counterparty losses on systemically important banks. 

In response to these events, policymakers around the world have launched a range of policy 
initiatives to contain risks from leverage in the NBFI sector more broadly (Table A). As the 
NBFI ecosystem comprises a wide range of entities performing different economic functions, with 
varying degrees of complexity in their use of leverage, authorities need to carefully choose and 
calibrate their measures. In doing so, they face certain trade-offs concerning, for example, the 
effectiveness of measures to target specific risks (e.g. procyclical deleveraging), their feasibility (e.g. 
complexity in their use) and potential costs (e.g. impact on hedging). This box provides an overview of 
recent policy initiatives aimed at addressing risks from NBFI leverage, including policy responses to 
the examples above. In other instances, policymakers have acted pre-emptively after identifying 
systemic vulnerabilities, as in the case of Irish real estate funds. 

Authorities in Ireland, Luxembourg and the United Kingdom have used entity-based 
measures to address leverage-related risks in government bond and real estate markets. In 
response to deleveraging by LDI funds in September 2022, authorities in the United Kingdom as well 
as in Ireland and Luxembourg, where a significant share of GBP-denominated LDI funds are 
domiciled, introduced entity-based measures to ensure a minimum level of resilience among these 
funds, which also acts to (indirectly) limit leverage.77  Moreover, authorities in Ireland have responded 
to heightened concerns regarding real estate risks by imposing macroprudential measures to mitigate 
the potential for deleveraging in these markets in times of stress. Irish authorities have introduced a 
leverage limit on borrowing of 60% for real estate funds, calculated as the ratio of a fund’s total debt to 
its total assets.78 

76    See the box entitled “Non-banks’ liquidity preparedness and leverage: insights and policy implications 

from recent stress events”, Financial Stability Review, ECB, May 2023. 

77    In the case of Ireland and Luxembourg, this tool is referred to as a “yield buffer”, which is set at between 
300 and 400 basis points, thus ensuring that the fund can absorb a corresponding increase in yields 
before its net asset value falls to zero. It can be seen as a measure to ensure minimum resilience, which 
indirectly affects leverage at LDI funds but does not impose a leverage limit as such. See “The Central 
Bank’s macroprudential policy framework for Irish authorised GBP-denominated LDI funds”, Central 
Bank of Ireland, April 2024, and “CSSF communication on macroprudential measures for GBP 
denominated Liability Driven Investment funds”, Communiqué, CSSF, April 2024. 

78    All new property funds will need to comply with this limit, while existing funds are granted up to five years 
to comply. See “The Central Bank’s macroprudential policy framework for Irish property funds”, Central 
Bank of Ireland, 24 November 2022. 

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In the United States, new rules mandating the central clearing of US Treasury (UST)-backed 
repos are part of a broader package to enhance UST market resilience. The U.S. Securities and 
Exchange Commission (SEC) has recently introduced rules mandating the central clearing of UST 
securities in repo transactions, which is an important example of an activity-based measure. This 
followed periods of turbulence in UST markets, which was partially driven by deleveraging of hedge 
funds engaging in basis trades. Moreover, the use of leverage by these funds was often facilitated via 
uncleared repo transactions, which were typically contracted with 0% haircuts. Due to the stricter risk 
management practices for cleared transactions (relative to the terms provided by prime brokers), the 
new rule will also help to ensure that higher haircuts are applied to such trades.79  The SEC has also 
introduced rules to improve the regulatory oversight of NBFI market participants that play a significant 
liquidity-providing role in overall trading and market activity in UST markets. These rules may also 
affect some large hedge funds.80 

The failure of Archegos Capital Management prompted global efforts to review the risk 
management practices of leverage providers and assess risks from “hidden” leverage. The 
collapse of Archegos in 2021 and the fallout in the banking sector raised serious questions regarding 
banks’ counterparty credit risk (CCR) management practices for their NBFI exposures.81  The ECB 
recently reviewed the CCR management practices of a sample of banks that are particularly active in 
providing prime brokerage services to NBFI entities and has issued guidance and outlined sound 
practices on areas such as governance, risk management and stress testing.82  In addition, the Basel 
Committee on Banking Supervision is currently reviewing its guidance on CCR regarding banks’ NBFI 
exposures.83  The Financial Stability Board has also examined the issue of “hidden” leverage in the 
financial system, which may lead to important policies to enhance transparency as part of a broader 
policy initiative to address NBFI leverage risks.84  In this light, joint work by the Federal Reserve 
Board, the Bank of England and the ECB to share information on their banking sectors’ NBFI 
exposures provides a useful example for how broader international efforts could improve 
transparency in cross-border and cross-sectoral exposures.85 

The examples presented in this box suggest that a broad and tailored set of policies is 
required to address the various risks posed by NBFI leverage. Authorities around the world have 
engaged in a wide range of policy initiatives to address risks posed by NBFI leverage. In doing so, 
they have needed to balance various trade-offs, which is reflected in their policy choices. A key 
takeaway from these recent experiences and policy initiatives is that no single tool can be uniformly 

79    See “Final rule: Standards for Covered Clearing Agencies for U.S. Treasury Securities and Application of 
the Broker-Dealer Customer Protection Rule with Respect to U.S. Treasury Securities”, U.S. Securities 
and Exchange Commission, 13 December 2023. 

80    See “Final rule: Further Definition of “As a Part of a Regular Business” in the Definition of Dealer and 
Government Securities Dealer in Connection with Certain Liquidity Providers”, U.S. Securities and 
Exchange Commission, 6 February 2024. 

81    In 2021 Archegos defaulted on portfolio losses related to highly leveraged and concentrated positions 
using total return swaps in equity markets. At the end of March 2021, bank losses linked to the failure 
totalled over USD 10 billion. 

82    See “Sound practices in counterparty credit risk governance and management”, ECB, October 2023, and 
“Supervisory expectations for prime brokerage services”, Supervision Newsletter, ECB, 17 August 2022. 
The ECB also identified counterparty credit risk as a broader supervisory priority in 2022. 

83  See “Basel Committee work programme and strategic priorities for 2023/24”, Basel Committee on 

Banking Supervision, 16 December 2022. 

84    See “The Financial Stability Implications of Leverage in Non-Bank Financial Intermediation”, Financial 

Stability Board, 6 September 2023. 

85    See “Supervising counterparty credit risk – a European perspective”, keynote speech by Elizabeth 

McCaul, Member of the Supervisory Board of the ECB, ECB, 28 February 2024. 

Financial Stability Review, May 2024 – Macroprudential policy issues 

90 

 
 
 
applied to address risks stemming from NBFI leverage. An effective policy response requires a broad 
range of tools to be made available, which should be appropriately tailored to the specific 
circumstances and can serve as complements to each other. Given the significant cross-border and 
cross-sector dimension of these risks, close coordination and cooperation between various 
authorities is essential, ensuring that risks are addressed from a system-wide perspective. 

Table A 
Authorities around the world are actively engaged in initiatives to contain risks from NBFI leverage 

Overview of policy measures 

Risk channel 

NBFI activities 

NBFI entities 

Leverage providers 

Transparency 

Policy measures 

Event/ 
vulnerability 

COVID-19 
market turmoil 
(March 2020) 

UK gilt market 
crisis 
(September 
2022) 

SEC proposals on 
mandating clearing of 
repos (part of broader 
package) 

Procyclical 
deleveraging by 
leveraged 
(multi-strategy) hedge 
funds in UST markets 

Procyclical 
deleveraging by LDI 
funds in UK gilt markets 

Excessive 
leverage among 
Irish real estate 
funds 

Potential procyclical 
deleveraging of funds 
in Irish property 
markets 

Archegos fallout 
(March 2021) 

Counterparty losses 
due to inadequate risk 
management and 
transparency 

Source: ECB.   

Indirect leverage limits 
for GBP-denominated 
LDI funds domiciled in IE, 
LU and UK 

Direct leverage limits for 
Irish real estate funds 
(phased-in for existing 
funds) 

ECB review of banks’ 
CCR practices 

BCBS review of its CCR 
management guidelines 

Cross-border 
information-sharing 
(BOE-ECB-FRB) 

International work on 
transparency and data 

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Special Features 

A 

Turbulent times: geopolitical risk and its impact on euro 
area financial stability 

Prepared by Daniel Dieckelmann, Christoph Kaufmann, Chloe Larkou, 
Peter McQuade, Caterina Negri, Cosimo Pancaro and Denise Rößler 

Geopolitical risk can be a threat to financial stability and the global economy. It can 
adversely affect the economy and financial markets and consequently have a negative 
impact on the funding, lending, solvency, asset quality and profitability of banks and 
non-banks alike. Recent history suggests that adverse geopolitical events alone are 
unlikely to cause a systemic crisis, although they may act as a trigger for systemic 
distress if they interact with pre-existing vulnerabilities. Looking ahead, policy 
authorities need to monitor geopolitical risk and assess its possible consequences for 
financial stability. Financial institutions should apply a combination of sound risk 
management and business diversification to address geopolitical risk. 

Introduction 

Geopolitical risk, which has increased of late, can be a threat to financial 
stability. Recent conflict in the Middle East, fears of an escalation in US-China 
tensions over Taiwan and the Russian invasion of Ukraine have all raised concerns 
about geopolitical stability. Adverse geopolitical events can trigger rapid shifts in 
market sentiment and sharp increases in uncertainty, exposing existing vulnerabilities 
in financial institutions and markets. Moreover, they can dent consumption and 
investment plans, with knock-on effects for economic growth, and activate adverse 
feedback loops between the real economy and the financial world. This special feature 
starts by providing a conceptual overview of the channels through which geopolitical 
risk can affect euro area financial markets, the economy and the financial sector. It 
then goes on to present empirical evidence on the effects of geopolitical risk on euro 
area non-banks and banks. 

Geopolitical risk is the threat, realisation and escalation of adverse events 
associated with wars, terrorism and tensions among states and political actors 
that affect the peaceful course of international relations. This definition is 
consistent with the geopolitical risk (GPR) index created by Caldara and Iacoviello and 
used in this special feature.86  Higher values for the GPR index suggest an increase in 
the likelihood or intensity of adverse geopolitical events, and vice versa. By contrast, 

86    See Caldara, D. and Iacoviello, M., “Measuring Geopolitical Risk”, American Economic Review, Vol. 112, 
No 4, April 2022, pp. 1194-1225. The GPR index is constructed by counting the number of newspaper 
articles related to adverse geopolitical events as a share of the total number of newspaper articles at a 
monthly frequency. The global GPR index is based on one Canadian, three UK and six US newspapers. 

Financial Stability Review, May 2024 – Special Features 

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the concept of geopolitical fragmentation is different – it captures the reversal of global 
economic and financial integration due to geopolitical considerations.87 

Channels through which geopolitical risk affects financial stability 

Geopolitical risk could adversely affect the global economy and spark financial 
instability through a variety of channels. On the real-economy side, geopolitical 
risk can impact the economy by negatively affecting real GDP growth, inflation, trade, 
investment, consumption and savings (Figure A.1). On the financial side, geopolitical 
risk can affect capital flows and asset prices, among other things, and lead to volatility 
in commodity markets, exchange rates, stock prices, interest rates and credit spreads. 
Given the linkages between the real economy and the financial sectors, feedback 
processes may reinforce direct effects. These adverse effects on the real economy 
and financial markets could have negative consequences for the funding, lending, 
solvency, asset quality and profitability of non-banks and banks. 

Figure A.1 
Transmission channels of geopolitical risk to financial stability 

Source: ECB staff. 

Geopolitical risk can have adverse effects on the economy. Adverse geopolitical 
events tend to increase uncertainty, causing a deterioration in investor and consumer 
sentiment that weighs on economic growth. In addition, international trade could also 
be curtailed as confidence is hit or trade restrictions and sanctions are increased. 
Furthermore, disruptions to global supply chains and commodity markets, such as the 
oil shocks in the 1970s that arose from geopolitical developments in the Middle East, 

87    For more on this topic, see “Global Financial Stability Report: Safeguarding Financial Stability amid High 

Inflation and Geopolitical Risks”, International Monetary Fund, April 2023. 

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may also have a negative impact on growth (Chart A.1).88,89  An empirical analysis 
estimating the effect of global geopolitical risks on macroeconomic variables suggests 
that inflation increases by almost 0.1 percentage points and industrial production 
declines by around 0.15% six months after a 1 standard deviation geopolitical shock 
(Chart A.2, panel a).90  In some circumstances, this could necessitate tighter 
monetary policy, which would have an adverse effect on financing conditions for firms 
and governments. 

Chart A.1 
Severe geopolitical risk events have often had large effects on oil prices 

Brent crude oil price and GPR index since 1970 

(Jan. 1970-Feb. 2024; left-hand scale: USD/barrel, right-hand scale: percentage share of all articles) 

Sources: Bloomberg Finance L.P., Energy Intelligence Group, OPEC, World Bank, and Caldara and Iacoviello*. 
*) Caldara, D. and Iacoviello, M., op. cit. 

Geopolitical risks could destabilise financial markets by increasing uncertainty 
and weighing on the macroeconomic outlook.91  Expectations of slower 
macroeconomic growth and higher inflation can weigh on the outlook for firm 
profitability. This, together with increased credit risk, would reduce equity and 
corporate bond valuations and raise the rates banks charge on loans, tightening 
financing conditions for non-financial corporations. The threat of adverse geopolitical 
developments can also increase financial market uncertainty more broadly, 
undermining confidence among investors and heightening risk aversion. Empirical 
estimates confirm that euro area financial variables react to geopolitical risk. The 
EURO STOXX 50 index is estimated to fall by around 1% on impact in response to a 

88    See Góes, C. and Bekkers, E., “The impact of geopolitical conflicts on trade, growth, and innovation”, 

Staff Working Papers, ERSD-2022-9, World Trade Organization, July 2022. 

89    See the box entitled “Geopolitical risk and oil prices”, Economic Bulletin, Issue 8, ECB, 2023; Caldara, D., 
Conlisk, S., Iacoviello, M. and Penn, D., “Do Geopolitical Risks Raise or Lower Inflation?”, mimeo, 2023; 
and Smith, S. and Pinchetti, M., “The transmission channels of geopolitical risk”, Bank of England, Bank 
Underground, 4 April 2024. 

90    For reference, the Russian invasion of Ukraine in 2022 was an event of roughly 5 standard deviations for 

the global GPR index. 

91    In the event of a war, governments may close financial markets − making it impossible to trade financial 
assets in the normal venues or exchanges − impose debt moratoria or suspend currency convertibility, 
while also seizing or requisitioning real or financial assets. Such extreme scenarios are not considered 
here. See Ferguson, N., “Earning from History? Financial Markets and the Approach of World Wars”, 
Brookings Papers on Economic Activity, Vol. 2008, Spring 2008, pp. 431-477. 

Financial Stability Review, May 2024 – Special Features 

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geopolitical shock of 1 standard deviation. The VSTOXX (an option-implied equity 
market volatility index) increases by around 1.5 index points in the same scenario, 
suggesting that geopolitical risk not only affects asset prices but also increases market 
uncertainty (Chart A.2, panel b).92  The effects of geopolitical risk events on financial 
markets are found to be strongest on impact, after which they tend to fade 
somewhat.93  However, the persistence of the effects on markets is likely to vary 
depending on the underlying geopolitical risk, with larger and longer-lasting tensions 
leading to more severe and more persistent effects. 

Financial market volatility may prompt investors to reduce the weight of riskier 
assets in their portfolios and potentially engage in flight-to-safety behaviour. 
Econometric estimates suggest that initially yields on risky assets go up (as reflected 
in widening corporate bond spreads) while those on safe assets, such as German 
sovereign bonds, go down in response to a geopolitical shock (Chart A.2, panel b). 
This is consistent with flight-to-safety behaviour, as also seen in the appreciation of 
the US dollar in response to rising geopolitical risk, which is consistent with its role as 
a safe-haven currency. 

Chart A.2 
The materialisation of geopolitical risk could push up inflation, reduce industrial 
production and lead to a deterioration in financial conditions 

a) Impulse responses of euro area economic 
variables to a geopolitical risk shock 

b) Impulse responses of financial indicators to 
a geopolitical risk shock 

(Jan. 2001-Dec. 2023; percentage points, percentages) 

(Jan. 2001-Dec. 2023; percentages, indices, basis points) 

Sources: ECB, Bloomberg Finance L.P. and ECB calculations. 
Notes: Impulse responses to a 1 standard deviation global geopolitical risk shock (Caldara and Iacoviello*), based on a Bayesian vector 
autoregression model with monthly data from January 2001 to December 2023. The shocks are identified using a Cholesky 
decomposition, with geopolitical risk ordered first. All values are statistically significant at levels of at least 10%, except where shaded. 
Panel a: results are based on a model including the GPR index, the VSTOXX index, the EURO STOXX 50, the two-year Bund rate, the 
corporate bond spread, euro area HICP inflation and euro area industrial production. Panel b: results are based on a baseline model 
including the GPR index, the VSTOXX index, the EURO STOXX 50, the two-year Bund rate (extended to the USD/EUR exchange rate) 
and the oil price volatility index in separate estimations. 
*) See Caldara, D. and Iacoviello, M., op. cit. 

92    Caldara, D. and Iacoviello, M., op.cit., find that the S&P 500 index falls by almost 5% after 12 months in 
response to a 2 standard deviation shock to the GPR index, with considerable diversity across industry 
lines. 

93    For instance, the Russian invasion of Ukraine triggered a large initial market reaction, yet many euro area 

financial markets recovered most of their initial losses after around a month. 

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Geopolitical risk can also have profound consequences for banks and 
non-banks. The following sections describe what can happen to banks and 
non-banks when geopolitical risk increases and presents empirical estimates of the 
magnitude of these effects. 

Non-banks are among the first to feel geopolitical stress 

Investors are exposed to geopolitical risk through their asset portfolios. The 
degree of vulnerability varies between the different industrial sectors and depending 
on firms’ geographical location and trade links. Businesses related to transport, the 
aircraft industry and specific areas of manufacturing, such as steel, are most 
vulnerable to geopolitical risk.94  Industries like technology and most types of 
manufacturing have an intermediate risk exposure, while the least exposed business 
lines include mining and consumer goods. Some sectors, such as fossil fuels, natural 
gas and defence, may even profit from geopolitical risk-related stress. 

Stock and bond exposures to industries most vulnerable to geopolitical risk are 
concentrated among non-banks. This exposure makes them vulnerable to market 
risk since asset valuations tend to fall when adverse geopolitical events occur 
(Chart A.2, panel b). Credit risk could also materialise when real economic activity 
deteriorates after an adverse event (Chart A.2, panel a). Investment funds hold more 
than €8 trillion in corporate stocks and bonds, of which around 10% are invested in the 
most vulnerable industry categories (Chart A.3, panel a). Banks’ holdings mainly 
consist of securities issued by other financial corporations – these are classified in the 
intermediate risk categories. Households’ exposures are more limited in absolute 
terms. Such direct securities investments only make up a relatively small share of their 
total wealth that also includes real estate assets and bank deposits, among other 
things. 

Investment funds’ exposure to valuation losses and credit risk could 
exacerbate financial stress stemming from geopolitical tensions. Investment 
fund returns tend to fall after geopolitical shocks and can be subject to sizeable 
investor redemptions (Chart A.3, panel b). The latter may induce investment funds, 
especially those with small cash positions, to sell assets, exacerbating any initial 
pressure on asset prices and, as a result, firms’ financing conditions. Equity funds 
experience sizeable and persistent outflows, although investors differentiate between 
fund types focusing on specific industries. Funds investing in financials and 
industrials, which include some of the sectors most heavily exposed to geopolitical 
risk, have immediate and persistent outflows (Chart A.3, panel b). At the same time, 
equity funds focusing on energy companies, and to a lesser extent commodities, 
receive strong inflows. This is consistent with the observation that the prices of fossil 
fuels and raw materials often rise when geopolitical tensions increase (Chart A.1). 

94    The classification is based on the response of the stock prices of different industry sectors to geopolitical 

shocks and is taken from Caldara, D. and Iacoviello, M., op. cit. 

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Chart A.3 
Stocks and bonds of industries vulnerable to geopolitical risk are held by non-banks 
that could withdraw their funding quickly 

a) Equities and corporate bonds, by holding 
sector and exposure to geopolitical risk 

b) Impulse responses of euro area-domiciled 
equity fund flows to a geopolitical risk shock 

(Q4 2023; left-hand scale: € trillions, right-hand scale: percentage 
shares of equity and corporate bond portfolios) 

(Jan. 2002-Dec. 2023; months after shock, percentage shares of 
funds’ total net assets) 

Sources: ECB (SHS, CSDB), EPFR Global, Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: equity and corporate bond holdings of euro area investors at market value, classified into heatmap of SIC-classified 
industry sectors’ exposure to geopolitical risk using stock returns following the methodology of Caldara and Iacoviello*. Most exposed 
sectors include transport, aircraft, steel works and electronics. Least exposed sectors include mining, petroleum and gas, defence and 
consumer goods. ICPFs stands for insurance corporations and pension funds; IFs stands for investment funds. Panel b: impulse 
responses to a 1 standard deviation global geopolitical shock (Caldara and Iacoviello*) based on a Bayesian vector autoregression 
model with monthly data from January 2002 to December 2023. All responses are based on separate models that include the GPR index, 
one category of cumulative flows into euro area-domiciled equity funds, the VSTOXX index, the EURO STOXX 50 and the two-year Bund 
rate. The shocks are identified using a Cholesky decomposition with geopolitical risk ordered first. All values statistically significant at 
levels of at least 10%. Estimation for industrials equity funds begins in March 2006 due to data availability. 
*) See Caldara, D. and Iacoviello, M., op. cit. 

Corporate bond funds are directly affected and experience both strong 
outflows and lower returns when geopolitical risk rises. Interest rates on 
sovereign bonds fall mildly on impact, while corporate bond spreads tend to rise, 
pointing to reduced risk appetite in financial markets (Chart A.4, panel a). Bond yields 
tend to rise in the months following a shock, implying that financing conditions are 
deteriorating for both firms and governments (Chart A.2, panel b). Returns on both 
corporate and sovereign bond funds fall in the wake of a geopolitical shock because of 
the asset valuation losses caused by the shock (Chart A.4, panel b). Specifically, a 1 
standard deviation shock decreases the returns of corporate and sovereign bond 
funds by almost 0.5 percentage points and 0.4 percentage points respectively after six 
months. At the same time, investors persistently withdraw from corporate bond funds, 
potentially forcing fund managers to sell assets. 

Sovereign bond funds receive sizeable inflows, pointing to flight-to-safety 
behaviour on the part of investors. This could support government financing needs, 

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which often rise in the context of geopolitical tensions.95  Interestingly, geopolitical 
stress does not lead to elevated fragmentation risks in euro area sovereign bond 
markets. Spreads between more and less indebted euro area sovereigns do not react 
significantly to geopolitical shocks (Chart A.4, panel a). Sovereign debt holdings of 
countries directly involved in conflicts could be subject to credit or repudiation risks if a 
belligerent decides not to honour its debt obligations to international investors, as was 
the case with Russian government debt during 2022. 

Chart A.4 
Geopolitical risk can trigger flight to safety and stress corporate bond markets 

a) Impulse responses of bond spreads to a 
geopolitical risk shock 

b) Impulse response of euro area-domiciled 
bond funds to a geopolitical risk shock 

(Jan. 2001-Dec. 2023, basis points) 

(Nov. 2003-Dec. 2023; x-axis: months after shock, y-axis: model 
responses to a 1 standard deviation shock, percentages) 

Sources: ECB (SHS, CSDB), EPFR Global, Bloomberg Finance L.P. and ECB calculations. 
Notes: Impulse responses to a 1 standard deviation global geopolitical risk shock (Caldara and Iacoviello*) based on a Bayesian vector 
autoregression model with monthly data. The shocks are identified using a Cholesky decomposition with geopolitical risk ordered first. All 
values are statistically significant at levels of at least 10%. Panel a: the model includes monthly observations from January 2001 to 
December 2023 for the GPR index, the VSTOXX index, the EURO STOXX 50, the two-year Bund rate, the European corporate bond 
market spread and the spread between ten-year Italian and German government bonds. Panel b: the model includes monthly 
observations from November 2003 to December 2023 for the GPR index, the VSTOXX index, the EURO STOXX 50, the two-year Bund 
rate and one category of cumulative returns or flows into euro area-domiciled bond funds, measured as a share of past total net assets. 
*) See Caldara, D. and Iacoviello, M., op. cit. 

Geopolitical risk can also have adverse implications for banks 

The vulnerability of euro area banks to geopolitical risk varies from institution 
to institution, depending on their actual exposure to adverse geopolitical 
developments. To evaluate the exposure of individual banks to geopolitical risk, we 
construct a new bank-level indicator of geopolitical risk which uses the GPR index and 
ECB supervisory data on banks’ asset exposures across countries. More specifically, 
the new indicator is built by weighting the standardised country-level geopolitical risk 
indices with bank-level asset-side exposure to the different countries where banks 

95    Caldara, D. et al., op cit., find that government debt and spending, including military expenditure, rise 

significantly after geopolitical risk materialises. 

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operate (Chart A.5, panel a).96  The indicator exhibits significant variation and peaks 
around the start of the Russian invasion of Ukraine.97  As expected, the peaks are 
especially high for banks operating in countries located closer to Ukraine and Russia 
as they face relatively higher levels of geopolitical risk (Chart A.5, panel b). The 
indicator exhibits other highs corresponding, for example, to the terrorist attacks in 
Paris in the third quarter of 2015, in Brussels in the first quarter of 2016 and in 
Germany in the first quarter of 2020. 

Chart A.5 
Euro area bank exposure to geopolitical risk spiked when Russia invaded Ukraine 

a) Bank exposure-weighted GPR index 

b) Average bank-level exposure-weighted 
GPR index at the time of the Russian invasion 
of Ukraine, by country 

(Q1 2015-Q3 2023, standard deviations from long-term average) 

(Q1 2022) 

Sources: ECB (supervisory data), Caldara and Iacoviello*, Factiva and ECB staff calculations. 
Notes: The exposure-weighted bank-level GPR index is constructed by weighting the country-level GPR indices with bank-level 
asset-side exposure shares to different countries, obtained from ECB supervisory data. The GPR index is available at the country level 
for 44 countries (including eight euro area countries). To make the analysis more comprehensive, we use the same methodology and the 
Factiva news monitoring platform to extend the coverage of the index to all missing euro area and EU countries, meaning that the 
analysis considers a total of 62 countries. This ensures that for all 73 euro area significant institutions considered in our sample, at least 
80% of their asset-side exposure is accounted for. Country-level GPR indices are weighted by asset-side geographical exposure shares 
divided by total assets. Moreover, to make levels more comparable across banks, we standardise the country-level GPR indices by 
transforming them into z-scores based on historical time series going back to 1985 (where available) before weighting them. Panel a: 
standard deviations for the GPR index are calculated in respect of the long-term average of the series (1985-2023). Panel b: darker 
colours indicate a higher average exposure-weighted GPR index for the country’s significant institutions. 
*) Caldara, D. and Iacoviello, M., op. cit. 

Geopolitical risk events can have an adverse impact on bank credit default 
swap (CDS) spreads and stock prices. Bank-level estimations show that there is a 
positive and statistically significant relationship between the bank-level GPR index 
and the CDS spreads of euro area banks. By contrast, stock prices are affected 
negatively. More specifically, the estimated coefficients suggest that a 1 standard 
deviation increase in the bank-level GPR index is significantly associated with an 
increase in CDS spreads of 38 basis points and a decline in stock prices of around 6% 
(Chart A.6, panels a and b). These results are driven primarily by weakly capitalised 
and less-profitable banks. The finding is consistent with the theory of geopolitical risk 

96    The notes to Chart A.6 explain how the bank-level GPR index is constructed. 
97    On average, 65% of euro area significant institutions’ asset exposures are domestic and the remaining 
35% are foreign. Foreign exposures are divided into intra-euro area (40% of total foreign exposures) and 
extra-euro area (60% of total foreign exposures). 

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triggering risk aversion, causing investors to sell assets and demand a higher return 
for bearing the risk associated with certain banks, especially those perceived as less 
resilient to adverse shocks due to their weaker solvency and profitability. 

The funding and liquidity positions of banks could also come under strain, 
undermining their stability.98  Geopolitical tensions triggering a rise in risk aversion 
could lead to reduced funding (including cross-border credit), a higher cost of funding 
and greater recourse to short-term funding. These effects could also result in 
heightened rollover risk and potential liquidity stress. Empirical evidence shows that 
there is a positive and statistically significant relationship between the bank-level GPR 
index and the bond yields of euro area banks. A 1 standard deviation increase in the 
bank-level GPR index is associated with an increase of 7 basis points in bond yields 
(Chart A.6, panel c). This result is also driven by weakly capitalised and less-profitable 
banks. 

Chart A.6 
Greater market reaction to geopolitical risk for weakly capitalised and less-profitable 
banks 

a) CDS spreads 

b) Stock prices 

c) Cost of funding 

(basis points) 

(percentages) 

(basis points) 

Sources: Eurostat and ECB (GFS, ICP, MNA), ECB (RTD, supervisory data), Bloomberg Finance L.P., LSEG, S&P Dow Jones Indices 
LLC and/or its affiliates, Caldara and Iacoviello*, Ahir et al.** and ECB staff calculations. 
Notes: Coefficient estimates indicate the effect on the dependent variable of a 1 standard deviation shock to the bank-level GPR index. 
Based on panel regressions on a sample of 34 significant institutions for CDS spreads, 31 institutions for stock prices and 37 institutions 
for cost of funding, from Q1 2015 to Q3 2023. The regressions control for lagged bank-level characteristics (equity/asset ratio, cost of 
risk, cost/income ratio, return on assets, total loans/deposits ratio) as well as the World Uncertainty Index99  and country-level 
macroeconomic variables (real GDP growth, inflation rate, stock market index, one-year sovereign bond yields). Regressions control for 
bank fixed effects and time (quarter) fixed effects. The regressions also include a dummy for Greek banks in the period 2015-16. All 
coefficient estimates are statistically significant at levels of least 10%, except where shaded. For the sub-sample analysis, banks with an 
equity/asset ratio above the median are considered highly capitalised (with high profitability) while banks with an equity/asset ratio below 
the median are considered to have low capitalisation (low profitability). 
*) Caldara, D. and Iacoviello, M., op. cit. 
**) Ahir, H., Bloom, N. and Furceri, D., op. cit. 

Banks may respond to geopolitical risk by raising lending rates and reducing 
risk by adjusting exposures and decreasing lending. Both credit supply and credit 
demand may be dampened by adverse macroeconomic developments caused by 

98    See Phan, D.H.B., Tran, V.T. and Iyke, B.N., “Geopolitical risk and bank stability”, Finance Research 
Letters, Vol. 46, Part B, 2022, and Banna, H., Alam, A., Alam, A.W. and Chen, X.H., “Geopolitical 
Uncertainty and Banking Risk: International Evidence”, SSRN Working Paper, No 4325966, 2023. 
99    See Ahir, H., Bloom, N. and Furceri, D., “The World Uncertainty Index”, Working Paper Series, No 29763, 

National Bureau of Economic Research, 2022. 

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geopolitical risk. On the credit supply side, greater uncertainty may make banks less 
willing to lend to non-financial corporations and households.100  On the credit demand 
side, households and corporations may be reluctant to take out loans or invest in times 
of elevated uncertainty. That said, the empirical evidence on the effect of geopolitical 
risk on bank lending is mixed. Some studies suggest that geopolitical risk is not 
associated with a reduction in overall bank lending.101  The effects on bank lending 
may also vary across sectors, as lending to households tends to be domestically 
focused while corporate lending may be targeted more towards export-oriented 
sectors. It may also be used to fund overseas investment or trade finance, and as such 
may be more exposed to foreign geopolitical risk. Banks’ efforts to reduce exposure to 
those sectors most affected by geopolitical risk could act as headwinds to economic 
activity in these sectors. For instance, international trade could be curtailed if banks 
decided to limit the availability of trade finance or increase its cost.102 

Chart A.7 
Geopolitical risk negatively affects bank profitability (especially for smaller and weakly 
capitalised banks) and asset quality (especially for smaller banks) 

a) Return on assets 

(basis points) 

b) Cost of risk 

(basis points) 

Sources: Eurostat and ECB (GFS, ICP, MNA), ECB (RTD, supervisory data), Bloomberg Finance L.P., LSEG, S&P Dow Jones Indices 
LLC and/or its affiliates, Caldara and Iacoviello*, Ahir et al.** and ECB staff calculations. 
Notes: Coefficient estimates indicate the effect on the dependent variable of a 1 standard deviation shock to the bank-level GPR index. 
Based on panel regressions on a sample of 71 significant institutions from Q1 2015 to Q3 2023. The regressions control for lagged 
bank-level characteristics (equity/asset ratio, cost of risk, cost/income ratio, return on assets (ROA), total loans/deposits ratio) as well as 
the World Uncertainty Index and country-level macroeconomic variables (real GDP growth, inflation rate, stock market index, one-year 
sovereign bond yields). Regressions control for bank fixed effects and time (quarter) fixed effects. For regressions with the ROA as the 
dependent variable, the ROA is omitted as an explanatory variable. Similarly, for regressions with the cost of risk as the dependent 
variable, cost of risk is omitted as an explanatory variable. All coefficient estimates are statistically significant at levels of at least 10%, 
except where shaded. For the sub-sample analysis, banks with an equity/asset ratio (total assets) above the median are considered 
highly capitalised (large) while banks with an equity/asset ratio (total assets) below the median are considered to have low capitalisation 
(small). 
*) Caldara, D. and Iacoviello, M., op. cit. 
**) Ahir, H., Bloom, N. and Furceri, D., op. cit. 

100   See Ashraf, B.N. and Shen, Y., “Economic policy uncertainty and banks’ loan pricing”, Journal of 

Financial Stability, Vol. 44, 2019. 

101   See Demir, E. and Danisman, G.O., “The impact of economic uncertainty and geopolitical risks on bank 
credit”, The North American Journal of Economics and Finance, Vol. 57, 2021, and Niepmann, F. and 
Shen, L.S., “Geopolitical risk and Global Banking”, mimeo, 2024. 

102   See Niepmann, F. and Schmidt-Eisenlohr, T., “No guarantees, no trade: How banks affect export 

patterns”, Journal of International Economics, Vol. 108, 2017, pp. 338-350. 

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The macroeconomic consequences of geopolitical risk could weaken bank 
asset quality. Slower economic growth could weaken the ability of borrowers to repay 
loans, thus leading to higher provisioning and more non-performing loans. For 
instance, there was a sharp increase in the average probability of default for bank 
loans to Russian and Ukrainian borrowers after Russia invaded Ukraine in 2022. 
Bank-level estimates show that increases in geopolitical risk result in weaker asset 
quality, measured by the cost of risk. The estimated coefficient suggests that a 1 
standard deviation increase in the bank-level GPR index is associated with a 7 basis 
point increase in the cost of risk (Chart A.7, panel b). The asset quality results are 
driven by the increase in the provisions of smaller banks, which are generally less 
diversified internationally and have less opportunity to spread their risk if their 
domestic market is exposed to geopolitical risk. 

Higher funding costs, weaker lending and a deterioration in asset quality 
arising from geopolitical risk could undermine bank profitability. A higher cost of 
funding could squeeze banks’ net interest margins, while lower loan volumes could 
reduce interest income. Loan losses and valuation losses on asset holdings could also 
weigh on profitability.103,104  Bank-level estimates show that a 1 standard deviation 
increase in bank-level geopolitical risk is significantly associated with a decline in bank 
profitability, measured by return on assets, of 9 basis points (Chart A.7, panel a). This 
result is driven by weakly capitalised and smaller banks, as they would likely 
experience higher funding costs and a more marked deterioration in asset quality in 
times of heightened geopolitical risk. 

Conclusions 

Recent history suggests that geopolitical shocks alone are unlikely to cause a 
systemic crisis, but the latest developments call for heightened vigilance.105 
The major geopolitical risk events of recent decades, such as the 9/11 attacks, did not 
immediately trigger financial crises, even in the countries directly affected by the 
events. In this context, recent history may not be a good guide to the severity of future 
shocks. Geopolitical shocks may act as a trigger for systemic distress if they interact 
with pre-existing vulnerabilities. In particular, financial instability could arise if a 
combination of different factors materialises, such as (i) a very large shock, (ii) other 
sources of amplification, and (iii) strong contagion. 

Geopolitical risk can have adverse implications for the resilience of financial 
institutions. Several academic and policy studies, as well as the empirical evidence 
reported in this special feature, suggest that the materialisation of geopolitical risk 
could have negative effects on the soundness of euro area banks and non-banks. 

103   Geopolitical risk could also increase the operational risks faced by banks. For instance, banks may be 
affected by the imposition of financial sanctions or legal requirements to seize foreign assets, while the 
risk of state-sponsored cyberattacks may increase. 

104   Hampered profitability could in turn contain bank capital accumulation, which would then lead to a lower 

supply of credit, dampening economic activity. 

105   See also Baron, M. and Dieckelmann, D., “Historical Banking Crises: A New Database and a 

Reassessment of their Incidence and Severity”, in Schularick, M. (ed.), Leveraged: The New Economics 
of Debt and Financial Fragility, University of Chicago Press, 2021, pp. 209-226. 

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Geopolitical risk could result in significant outflows and falling returns from investment 
funds, among other things. Equally, geopolitical risk could lead to declining bank stock 
prices, widening CDS spreads and greater funding costs and provisioning needs for 
banks, which in turn would weigh on their profitability. 

Policy authorities need to monitor geopolitical risk and assess its possible 
consequences for financial stability. Assessing these risks will enable policy 
authorities to enhance their ability to identify vulnerabilities, better understand how 
geopolitical events might propagate through the financial system and draw up possible 
policy responses in advance. This would facilitate a swift and coordinated policy 
response when needed and strengthen the overall resilience of the financial system. 

Financial institutions should apply a combination of risk management 
strategies and business diversification to address geopolitical risk. First, 
institutions need to have robust capital adequacy and liquidity management 
frameworks in place to withstand shocks, including those arising from possible 
geopolitical risk events. Institutions should also set up dedicated teams or utilise 
specialised services to continuously monitor geopolitical developments. Such a 
proactive approach would allow them to anticipate risks and adjust their strategies 
accordingly. They should regularly assess their resilience to geopolitical risk by 
carrying out dedicated and thorough assessments and stress tests. Additionally, they 
could purchase political risk insurance to protect themselves against losses resulting 
from geopolitical events. Finally, financial institutions should develop robust 
contingency plans so that they can respond swiftly to unexpected events and minimise 
disruption to their operations. 

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B 

The rise of artificial intelligence: benefits and risks for 
financial stability 

Prepared by Georg Leitner, Jaspal Singh, Anton van der Kraaij and 
Balázs Zsámboki106 

The emergence of generative artificial intelligence (AI) tools represents a significant 
technological leap forward, with the potential to have a substantial impact on the 
financial system. Conceptually, AI brings both benefits and risks to the financial 
system. Practically, the overall impact will depend on how the challenges related to 
data, model development and deployment are addressed – both at the level of 
financial institutions and for the financial system as a whole. If new AI tools are used 
widely in the financial system and AI suppliers are concentrated, operational risk 
(including cyber risk), market concentration and too-big-to-fail externalities may 
increase. Furthermore, widespread AI adoption may harbour the potential for 
increased herding behaviour and market correlation. Should concerns arise that 
cannot be tackled by the current regulatory framework, targeted initiatives may need 
to be considered. 

Introduction 

Since late 2022 public interest in AI has increased sharply, and the volume of 
AI-related jobs, innovations and patents is growing constantly. Google searches 
for AI-related terms have surged since the launch of ChatGPT. At the same time, the 
number of AI-related jobs, AI models and patents connected to AI is growing 
constantly. Most of the recently launched models are language or multimodal models, 
and in recent years Europe has had more people working in AI-related roles than the 
United States (Chart B.1). According to a recent study, 64% of businesses believe 
that AI will increase their productivity, while 40% of business owners are concerned 
about technology dependence.107  Other estimates show that among industries 
globally, generative AI could add the equivalent of between USD 2.6 trillion and USD 
4.4 trillion of economic value annually. Banking is expected to be a large 
beneficiary.108,109 

106   With contributions from Nicola Doyle. 
107   Case study conducted among 600 business owners. See Haan, K., “How Businesses Are Using Artificial 

Intelligence In 2024”, Forbes Advisor, April 2023. 

108   See Kamalnath, V. et al., “Capturing the full value of generative AI in banking”, McKinsey & Company, 

December 2023. 

109   Banking is expected to have an annual potential of USD 200 billion to USD 340 billion of added economic 
value (equivalent to 9-15% of operating profits), largely from increased productivity. See Chui, M. et al., 
“The economic potential of generative AI: The next productivity frontier”, McKinsey & Company, June 
2023. 

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Chart B.1 
Attention on AI has spiked and AI-related jobs, innovations and patents are increasing 

a) Professionals employed in AI roles, by 
region, and AI-related Google search trends 

b) Number of notable AI systems and sum of 
AI and machine learning patents of the largest 
patent owners 

(Jan. 2014-Dec. 2023; thousands, index) 

(2014-23; AI systems in absolute numbers and patents in 
thousands) 

Sources: Google Trends, State of European Tech*, Epoch**, Statista*** and ECB calculations. 
Notes: Panel a: Google search trends represent monthly global search interest relative to the highest point, indicated by the value 100 
and for each search term. Figures on AI jobs comprise all companies, non-tech included, based on an analysis of the job titles of 216 
million professionals. The universe of professionals considered to be actively employed in AI/ML roles is based on a search utilising both 
common job titles in the field (e.g. AI researcher, ML engineer) and key phrases used in job titles (e.g. deep learning). Panel b: patents 
are cumulative over the ten largest patent owners (one South Korean, two US and seven Chinese companies and institutions) in 
machine learning and AI worldwide from 2013 to 2022 and are lagged by one year in the plot “Number of notable AI systems”. The 
authors of the Epoch dataset have established a set of criteria used to identify key AI systems which they refer to as “notable”. Such 
systems must demonstrate the ability to learn, show tangible experimental results and contribute advancements that push the 
boundaries of existing AI technology. In terms of notability, the AI must have garnered extensive academic attention, evidenced by a high 
citation count, hold historical significance in the field, mark a substantial advancement in technology or be implemented in a significant 
real-world context. The authors recognise the difficulty of evaluating the impact of newer AI systems since 2020 given the fact that less 
data are available for the period. They therefore also employ subjective judgement when selecting recent developments. 
*) “Embrace risk, shape the future”, State of European Tech, 2023.   
**) Epoch (2024) – with minor processing by Our World in Data. “Annual number of AI systems by domain” [dataset]. Epoch, “Parameter, 
Compute and Data Trends in Machine Learning” [original data]. 
***) Wunsch, N.-G., “Companies with the most machine learning & AI patents worldwide 2013-2022”, Statista, April 2023. 

The pace and scale of AI, like any sweeping innovation, is likely to bring 
benefits but could also pose risks for financial stability. International 
standard-setters and regulatory authorities have intensified their efforts regarding the 
consequences of AI for the financial system.110  There is a broad consensus that the 
use of AI is associated with possible benefits for numerous sectors, including the 
financial sector. It is therefore no surprise that euro area banks are exploring and 
using innovative technologies such as AI to support their digital transformation 

110   See, for example, Yong, J. and Prenio, J., “Humans keeping AI in check – emerging regulatory 

expectations in the financial sector”, FSI Insights, No 35, Bank for International Settlements, August 
2021; “Artificial Intelligence and Machine Learning”, Discussion Paper, No 5/22, Bank of England, 
October 2022; Shabsigh, G. and Boukherouaa, E.B., “Generative Artificial Intelligence in Finance”, 
International Monetary Fund, August 2023; “Artificial intelligence and machine learning in financial 
services”, Financial Stability Board, November 2017, and as part of the FSB Work Programme for 2024,a 
follow up report on AI and their potential implications for financial stability. The EU is establishing the 
European Artificial Intelligence Board under the Artificial Intelligence Act and the European AI Office; the 
United Nations has established an AI Advisory Body; for the United States, see the Select Committee on 
AI and the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial 
Intelligence. 

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(Chart B.2, panel b). At the same time, there could also be AI risks for financial 
institutions and, potentially, the wider financial system.   

This special feature provides a conceptual framework for assessing the 
systemic implications of AI for the financial system. To this end, the feature first 
investigates how the benefits and risks for individual financial institutions using AI are 
related to the technological aspects of AI. Next, it assesses how these benefits and 
risks at the firm level could unfold at the macro level, potentially leading to implications 
for financial stability. 

What is AI? 

AI is a broad term including various sub-fields and technological concepts. AI 
comprises two broad strands (Figure B.1)111: (1) data-driven machine learning 
systems; and (2) rule-based approaches such as deterministic chatbots, built on 
if/else instructions. Machine learning contains traditional statistical models and 
artificial neural networks. A hallmark of such networks is that they aim to replicate the 
learning process of the human brain. These models can capture non-linear properties 
of data and apply previously gained knowledge to new problems. Recently, the 
capabilities of artificial neural networks have been significantly boosted by increasing 
their complexity and training them on a vast amount of data. The rise of this new class 
of models, generally called foundation models,112  was mainly enabled by the 
decreasing cost and increasing efficiency of computational power.113 

Foundation models form a knowledge base for generative AI. These models are 
“trained” in a self-supervised114  manner on a vast amount of both structured (e.g. 
tables) and unstructured (images, sound, text) raw data with only minimal human 
intervention. In the pre-training phase, the model learns the fundamental structure 
(“ground truth”) of the data in a generic way, covering aspects like use of human 
language, recognition of objects and images, and numerical input. Generative AI 
models can make use of the generic knowledge of foundation models.115  A key 
feature of generative AI is its ability to produce unique output in the form of text, 
images and audio which share some properties of the input data but differ in others 
(generative capabilities). Most current generative AI models are based on text (large 
language models, or LLMs), thus eliminating the need for proficient coding skills to 

111   The overview aims to capture only the sub-fields of AI relevant for financial stability – it omits other 

sub-fields. Alternative approaches consider the two broad categories to be (1) weak AI or narrow 
intelligence (ANI), and (2) strong or general AI. (1) describes algorithms which are designed for a narrow 
task and try to mimic human behaviour. (2) defines algorithms which match and exceed human 
intelligence. There is a broad consensus that all AI technologies are currently weak AIs.   

112   See Bommasani, R. et al., “On the Opportunities and Risks of Foundation Models”, ArXiv, Cornell 

University, 2021. The definition of foundation models is based on the author’s definition.   

113   See Paunov, C. et al., “On the concentration of innovation in top cities in the digital age”, OECD Science, 

Technology and Industry Policy Papers, OECD, December 2019. 

114   Self-supervision in machine learning utilises unlabelled data. Unlike labelled data, which provide 

indicators for predictions, unlabelled data lack these labels. Algorithms employing self-supervision 
initially discern patterns and structures in unlabelled data, then proceed to label the data themselves. 

115   The pre-training on vast amounts of data is used to pre-calibrate the weights in the artificial neural 
network. The pre-calibration defines the “knowledge” of the artificial neural network (the foundation 
model) and can be used for generative AI models serving different specific downstream tasks. 

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modify or use them. The performance of foundation models can be enhanced by 
providing additional training on task-related data (fine-tuning) or by embedding 
additional tools like search engines. 

Figure B.1 
Systematic overview of AI and sub-fields 

Source: ECB analysis. 
Notes: This chart shows a possible systematic overview of AI and its sub-fields to facilitate understanding and distinguish different 
sub-fields of AI. Although its purpose is to facilitate an understanding and an evaluation of the impact of AI on financial stability, the 
overview could be extended to a more granular level for other use cases (e.g. distinguishing AI in machine learning, robotics, vision etc.) 
).There is no clear scientific taxonomy of AI and its sub-fields at this stage, but this chart represents a possible classification, which is in 
line with scientific discussions and approaches. For the distinction between AI and machine learning, see Das, S. et al. “Applications of 
Artificial Intelligence in Machine Learning: Review and Prospect”, International Journal of Computer Applications, Vol. 115, No 9, 2015. 
The paths from machine learning, artificial neural networks (ANNs) and deep learning mostly follow the definition found in Montesinos, L. 
et al., “Fundamentals of Artificial Neural Networks and Deep Learning”, Multivariate Statistical Machine Learning Methods for Genomic 
Prediction, Springer, Cham, 2022. For the definition of foundation models and their connection to generative AI, see, for example, 
Bommasani, R. et al., “On the Opportunities and Risks of Foundation Models”, ArXiv, 2021. 

Henceforth, when discussing AI we will generally refer to foundation models 
and generative AI. Foundation models and the generative AI models based on such 
models add new aspects to consider when assessing implications for the financial 
system. Therefore, this discussion focuses explicitly on these models. 

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Although AI has made significant progress, its cognitive limits should be 
acknowledged. Generative AI models have been referred to as “stochastic 
parrots”.116  The language they generate is often hard to distinguish from human 
interaction, yet in essence it is the outcome of a stochastic process that combines text 
based on probabilistic information. The term artificial intelligence may thus be a 
misnomer as it suggests “intelligence”, whereas in fact the model does not 
fundamentally understand the underlying logic of the text.117 

Benefits and risks of AI for financial institutions 

It is challenging to establish a comprehensive assessment of the implications 
of AI for the financial system as the technology is still evolving. Accordingly, any 
discussions of the benefits, risks and systemic consequences of AI are largely based 
on conjecture. That said, a preliminary view can be drawn from the latest trends, 
concepts and debates in publications, industry reports and ECB market intelligence 
reports.118 

The benefits and risks of AI depend on the use case. The development and 
deployment cycle (Figure B.2) establishes a conceptual framework for a structured 
assessment of the benefits and risks stemming from AI at the level of individual 
financial firm. Three main building blocks are required to apply AI to a specific use 
case: training data, the model itself and the deployment or implementation of the tool. 

Although AI greatly enhances the processing and generation of data, it may be 
prone to significant data quality issues. AI systems based on foundation models 
can process and analyse unstructured data beyond numerical input. These data 
include text, computer code, voice and images. AI can also be used to manage and 
create data.119  However, the way foundation models are trained means that they may 
be more likely to “learn” and sustain biases or errors inherent in the data they have 
been trained on. Hence, foundation models may be prone to data quality issues.120 
One additional challenge concerns data privacy, notably whether publicly available 
systems respect user input data privacy (which could, for instance, also be confidential 
firm-specific information) and whether there is a risk of data leakage. 

116   See Bender, E.M. et al., “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?”, 

Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, March 2021, 
pp. 610-623. 

117   See Perez-Cruz, F. and Shin, H.S., “Testing the cognitive limits of large language models”, BIS Bulletin, 
No 83, Bank for International Settlements, January 2024. The analysis suggests that caution should be 
exercised in deploying LLMs in contexts that demand rigorous reasoning in economic analysis. 

118   For further considerations, see among others Shabsigh, G. and Boukherouaa, E.B., op. cit.; Anderljung, 
M. et al., “Frontier AI Regulation: Managing Emerging Risks to Public Safety”, ArXiv, Cornell University, 
November 2023; Bommasani, R. et al., op. cit.; Yong, J. and Prenio, J., op. cit.; “Artificial Intelligence and 
Machine Learning”, Bank of England, October 2022; “Artificial intelligence and machine learning in 
financial services”, Financial Stability Board, November 2017; and Lorica, B. “Generative AI in Finance: 
Opportunities & Challenges”, Gradient Flow, August 2023. 

119   This could entail the creation of not only synthetic data – which could make the training of new models 

more affordable – but also measured data. 

120   In general, any AI output drawn from a data-based application depends on the quality of the data. If AI 
models, including machine learning and deep learning models, rely heavily on data that are biased, 
incomplete or contain errors, then the AI model will likely produce unreliable or biased results. 

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Figure B.2 
The AI development and deployment cycle – a conceptual framework for a structured 
assessment of the benefits and risks to financial system 

Source: ECB analysis. 
Notes: The first part of Figure B.2 describes the different phases in the development and deployment of an AI system, mentioning 
possible opportunities and challenges. opportunities and challenges are inherited throughout the phases and only take specific form in 
terms of benefits and risks, depending on the final use case. The table showing use-case-specific benefits and risks could change in the 
future, depending on technological developments and how institutions use the technology.   

AI models are adaptable, flexible and scalable, but prone to bias, hallucination 
and greater complexity, which makes them less robust. The general-purpose 
base architecture of AI can be fine-tuned to perform more specialised tasks. This can 
be achieved by training the model on specific data, for instance. This feature 
significantly enhances a model’s capabilities in a targeted area while retaining its 
overall generative capabilities. AI is thus adaptable and scalable for different use 
cases.121  That said, AI is prone to algorithmic bias, whereby the model systematically 
favours certain outcomes which have inequitable results. It may also present false or 
misleading information as facts – known as “hallucinations”.122  As recent AI models 

121   See Bommasani, R. et al., op. cit. The authors extensively discuss and explain the adaptable, flexible and 

scalable features of AI. 

122   Some studies find factual errors in up to 46% of generated outcomes. See, for example, de Wynter, A. et. 

al., “An evaluation on large language model outputs: Discourse and memorization”, Natural Language 
Processing Journal, Vol. 4, September 2023. 

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are much more complicated than traditional models, it is very difficult for humans to 
comprehend and reconstruct the predictions made.123  Furthermore, as AI may not be 
trained on the most recent information available, its capabilities may be limited by a 
technological knowledge cut-off. Together, these challenges strongly limit the 
robustness of AI predictions. 

When deployed, AI can increase efficiency, but its performance is difficult to 
predict and subject to possible misuse or overreliance. Thanks to AI’s inherent 
flexibility, it is expected that financial institutions will be able to deploy AI tools in a 
large variety of use cases, including tasks that have so far been performed by human 
labour. This is likely to result in greater efficiency and significant cost savings. At the 
same time, such deployment in new tasks and processes presents a risk, as it is 
difficult to predict and control ex ante how AI will perform in practice. AI systems can 
develop unexpected, potentially harmful capabilities when applied to new use 
cases.124  Furthermore, it is not inconceivable that AI could be misused in a harmful 
manner. For example, criminals could fine-tune and spoil otherwise harmless AI for 
specific operations (e.g. cyberattacks, misinformation, market manipulation, use of 
deep fakes to undermine confidence in a financial institution, etc.), increasing their 
threat potential. 

Financial institutions can be expected to deploy AI in several ways. In view of the 
enhanced capabilities of AI and the wealth of data available for financial institutions 
from which predictions can be made or new information generated, AI models could 
be usefully deployed in quantitative analysis, operational processes, risk 
management, client interaction and cybersecurity, among other areas. Given the rapid 
developments in these areas, the suggested conceptual framework does not exclude 
possible further use cases or alternative classifications. 

AI may improve the processing of information and the accuracy of quantitative 
predictions, but the robustness of its predictions remains a challenge. AI’s 
flexibility in analysing various forms of input data, together with its generative and 
predictive capabilities, will allow financial institutions to use it for data management, 
data creation and assessment functions. As such, AI could be used to systematically 
extract and prepare information in real time from various sources simultaneously 
(media, industry reports, conversations, market data, etc.) that can be used to form 
predictions. This could significantly improve the available information, leading to more 
precise decision-making and hence better outcomes (e.g. in trading, asset allocation, 
etc.). However, hallucination, algorithmic bias and vulnerability to data quality issues 
present risks to the accuracy of AI predictions. If financial entities base their decisions 
on faulty AI predictions which are not checked, this could lead to outcomes that may 

123   Often referred to as AI’s black box problem (see “AI’s mysterious ‘black box’ problem, explained”, 

University of Michigan-Dearborn, 6 March 2023). This further relates to a more fundamental discussion 
on the trade-off between accuracy and explainability. More complex model structures may achieve more 
accurate predictions which are, however, difficult to explain. On the other hand, simpler models can be 
more transparent, although they may be less accurate. 

124   AI system capabilities might depend on the concrete deployment of foundation models. Post-deployment 
enhancements, such as fine-tuning or allowing models to use external tools (like internet connection), 
can reveal new capabilities that are potentially dangerous or unexpected. See, for example, Anderljung, 
M. et al., op. cit. 

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result in economic losses or even disorderly market moves. Furthermore, the 
complexity of AI could make it difficult to identify the root cause of errors or explain and 
justify any decision based on AI.125   

AI may improve the efficiency of financial institutions’ operational processes, 
but operational risk and third-party dependence may increase. AI could be 
applied in various internal operational processes. These could range from co-piloting 
functions that automatically proofread or complete drafting text or coding, to more 
sophisticated algorithms (e.g. chatbots or digital assistants) that can automate routine 
tasks or entire workstreams.126  These applications would free up human resources, 
improve cost structures and potentially reduce human-induced error. On the other 
hand, data-, model- and deployment-related challenges may undermine AI’s 
robustness and, if AI is used to back up critical operational processes, this could 
significantly increase operational risk. Furthermore, depending on whether financial 
institutions have the in-house capacity to develop foundation models, the base 
architecture may need to be acquired from external companies. This will increase 
third-party reliance and could also raise data privacy concerns if the models provided 
by third parties are fine-tuned using confidential internal data (e.g. internal records, 
financial statements, etc.). 

AI could enhance the risk management functions of financial firms, but could 
also weaken them if its predictions prove unreliable. Risk management functions 
could be seen as sub-groups of the areas of quantitative analysis and operational 
processes. AI in this domain could be used for fraud detection and monitoring (e.g. for 
anti-money-laundering purposes), for capital and liquidity risk monitoring and 
planning, and for regulatory compliance.127  The considerations that apply to any 
AI-based quantitative analysis in terms of expected benefits and risk similarly apply to 
its deployment in risk functions. AI could enhance risk management capabilities, 
leading to more accurate risk assessment and predictions and more efficient capital 
and liquidity planning. At the same time, algorithmic bias, hallucination and other 
challenges could make institutions’ risk assessments that rely on AI less reliable and 
robust. Any benefits or risks that can be implied from AI use in risk management will 
have direct implications for the resilience of the financial sector from a prudential point 
of view, necessitating close monitoring by all stakeholders, including financial 
institutions’ management bodies and supervisory authorities. 

AI in customer-facing operations may improve the product-to-customer match, 
but its use could also lead to customer discrimination if it goes unchecked. It is 
expected that AI will unlock multiple new applications in customer-facing activities. 
These could be in communication, onboarding and complaints management (e.g. 
using automated chatbots), advisory functions (e.g. using digital 
assistants/robo-advisors) or for customer segmentation and targeting. AI will be able 

125   This also raises the question of who is accountable in the event of a malfunction with unforeseen 

consequences. 

126   Examples could include the gathering and documentation of information for internal reporting purposes, 

complaints management, legal assistance, HR processes, staff training, IT support lines, etc. 
127   This also includes applications used by institutions to facilitate regulatory compliance (regtech), but 

supervisory authorities may also enhance supervision processes with AI (suptech). 

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to better analyse a variety of customer-related data which could lead to better tailored 
products and services. This could improve financial institutions’ product-to-customer 
match, increasing economic efficiency for both the institution and the customer.128 
However, algorithmic bias may lead to discriminatory customer treatment and be 
difficult to identify and monitor. Furthermore, the issue of data leakage is particularly 
sensitive in the case of AI trained on customer-specific data, raising consumer 
protection considerations, and could also expose institutions to increased reputational 
or legal risk. 

Financial stability implications of AI 

The implications of AI for individual firms can become amplified to a systemic 
level through technological penetration and supplier concentration. There are 
two systemic amplifiers through which the implications of AI for single firms could 
become systemic. The first amplifier is technological penetration. If AI is widely 
adopted across different financial entities for an increasing number of processes and 
applications, more areas of the financial system will be affected by the challenges and 
opportunities associated with AI. The second amplifier is supplier concentration.129  If a 
majority of financial institutions use the same or very similar foundation models 
provided by a few suppliers, it is likely that decisions based on AI will suffer from 
similar biases and technological challenges, and reliance on system providers will 
increase. The interplay between these two dimensions will determine whether or not 
the benefits and risks stemming from use cases at individual institution level become 
systemic (left side of Figure B.3). 

Financial stability could be at risk if supplier concentration and technological 
penetration are high. On the one hand, if only a few institutions use AI and there are 
a large number of different providers of the technology, risks may occur at the micro 
level, depending on the use cases of individual institutions. On the other hand, if 
technological penetration and supplier concentration are high, any risk from AI that is 
relevant at the micro level could be amplified and lead to financial stability 
consequences. The transition from micro to macro could be gradual, but not 
necessarily linear. 

128   Overall efficiency could be increased not only by financial institutions deploying AI but also by customers 
themselves relying on third-party AI advisors to find the cheapest financial products from different 
providers, for instance. This greater transparency could translate into lower margins for banks but higher 
overall efficiency. 

129   Supplier concentration on the AI market can be seen as a result of rising oligopoly-like structures, which 
can already be observed e.g. on the market for cloud computing providers. See Narechania, T. N., and 
Sitaraman, G., “An Antimonopoly Approach to Governing Artificial Intelligence”, Vanderbilt Law Research 
Paper, No 24-9, November 2023 and Joy, M., “How Cloud Computing Companies Created an Oligopoly”, 
OnSIP, May 2021 

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Figure B.3 
Systemic amplifiers of AI and financial stability challenges 

Source: ECB analysis. 
Notes: The left side of the chart shows how the interplay between the widespread use of AI (technological penetration) and supplier 
concentration of AI models can raise institution-level benefits and risks, as described in Figure B.2, to a systemic level. Different 
combinations result in different levels of systemic relevance. Systemic relevance increases with technological penetration and supplier 
concentration, but not necessarily on a straight-line basis. For illustration purposes, it has been shown as linear here. If systemic 
relevance is given, then institution-specific benefits and risks can result in financial stability challenges, which can broadly be categorised 
into three buckets. Given the future technological development and use of AI by financial institutions, other financial stability 
consequences could arise through these three main channels. The risks listed above may be even larger for proprietary and 
non-auditable systems. 

Overreliance and a limited number of AI suppliers may make the operational 
backbone of the financial system more fragile. To leverage potential efficiency 
gains, financial institutions may increasingly substitute AI resources for human 
resources, potentially inducing an overreliance on AI in core functions that could 
render the financial system more vulnerable to inherent operational flaws and failures 
or cyberattacks. Both would be amplified if the number of AI suppliers is limited, as this 
would additionally increase the financial system’s dependency on third-party providers 
and introduce single-point-of-failure risks. This constitutes a potential threat to 
financial stability from the perspective of operational risk and cyber risk (Box A). 

The widespread adoption of AI may increase market concentration in the 
financial services industry. The integration of AI into business structures may 
require large initial fixed investments and entail economic risks. It may be easier for 
larger firms with well-established data infrastructure and third-party networks to obtain 
the requisite technological knowledge and levels of data availability. Accordingly, 
some financial institutions may miss the transition or be unable to make the necessary 
investments, ending up permanently behind and dropping out of the market. Like other 
information technology, AI may prove to be a winner-takes-all market. AI may thus 
contribute to a further shift in market power amid an increasingly digitalised 
environment, leading to a higher concentration in the financial system, among either 
existing players or new players (e.g. from the technology industry). Ultimately, this 

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could result in fewer institutions remaining on the market, accelerate too-big-to-fail 
externalities130  and transfer economic rents from consumers to financial institutions. 

AI may distort the information processing function of markets, increasing 
financial markets’ endogenous crisis potential. Conceptually, AI can be thought of 
as a filter through which information is gathered, analysed and assessed. The 
interpretation of information may become more uniform if increasingly similar models 
with the same embedded challenges and biases are widely used to understand 
financial market dynamics. As a result, AI may make market participants’ conclusions 
systematically biased, leading to distorted asset prices, increased correlation, herding 
behaviour or bubbles. Should many institutions use AI for asset allocation and rely 
only on a few AI providers, for example, then supply and demand for financial assets 
may be distorted systematically, triggering costly adjustments in markets that harm 
their resilience. Similarly, extensive use of AI by retail investors may result in large and 
similar shifts in retail trading patterns, which would increase volatility in market 
sentiment, trading volumes and prices. 

It is difficult to predict what level of technological penetration and supplier 
concentration AI will reach in the financial system. Just over half of the investment 
in AI firms was in four companies (Chart B.2, panel a), indicating a high degree of 
supplier concentration. Whether AI will be widely used in the financial system will 
depend on the expected benefits and return on investment.131  A survey of banks 
supervised by the ECB indicates that the majority of banks are already using 
traditional AI systems (Chart B.2, panel b).132  133  ECB market intelligence suggests, 
however, that the use of generative AI is still in the early stages of deployment. Market 
contacts indicate that euro area financial institutions may be slower to adopt 
generative AI, given the range of previously discussed risks,134  making the decision to 
be an early adopter or follower more complex in finance than in other sectors, also 
considering potential reputational risks. In addition, the technological adoption 
strategy implies a complex trade-off between partnering with external suppliers 
(including big tech firms as opposed to smaller start-ups) and establishing in-house AI 
expertise. The latter may become more feasible if more AI base architecture becomes 
available as open source. Ultimately, it is these decisions that will determine the levels 
of technological penetration and supplier concentration. 

130   See, for example, Bernanke, B.S., “Causes of the Recent Financial and Economic Crisis”, Testimony, 
Federal Reserve, September 2010, who defines the too-big-to-fail externality like this: “A too-big-to-fail 
firm is one whose size, complexity, interconnectedness, and critical functions are such that, should the 
firm go unexpectedly into liquidation, the rest of the financial system and the economy would face severe 
adverse consequences.” 

131   According to an ESMA study, market participants in the euro area are increasingly using AI in investment 

strategies, risk management, compliance, data analysis and post-trade processes. See “Artificial 
intelligence in EU securities markets”, ESMA TRV Risk Analysis, ESMA, 1 February 2023. 

132   See “Banks’ digital transformation: where do we stand?”, Supervision Newsletter, ECB, February 2023. 
133   This survey does not capture generative AI tools based on foundation models. 
134   From a financial stability perspective, concerns centred in particular on concentration risk arising from the 
limited number of vendors possessing the capabilities and technology to provide generative AI solutions, 
the scale of investment required (which some felt could favour large incumbents), data protection, the 
clustering of decision patterns, herding behaviour and cybersecurity. 

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Chart B.2 
Investments in AI start-ups are concentrated among a few companies and European 
banks are already relying on traditional AI 

a) Share of total private equity and venture 
capital raised by AI start-ups 

b) Adoption rates of innovative technologies 
by banks (excluding generative AI) 

(Dec. 2023) 

(Q3 2022, percentages) 

Sources: ECB and PitchBook Data, Inc. 
Notes: Panel a: shares represent the total amount of private equity and venture capital raised by individual AI start-ups to December 
2023. Only AI start-ups that are actively financed with private equity or venture capital, raised at least €100 million and are classified by 
PitchBook as working on horizontal platforms are considered. PitchBook’s definition of horizontal platforms is as follows: “Horizontal 
platforms empower end users to build and deploy AI&ML algorithms across a variety of use cases. Some horizontal platforms are used to 
improve AI&ML algorithms but do not use AI&ML themselves.” 175 start-ups are grouped together under “Other companies”. The total 
capital raised also includes financing before the recent innovations around generative AI, meaning that the concentration shown can be 
seen as a lower limit of concentration among generative AI and foundation model suppliers, as the largest and explicitly named 
companies work on generative AI. Panel b: Cloud comprises migration/IT optimisation and data platforms using software-as-a-service 
(SaaS) solutions; AI comprises chatbots, credit scoring and algorithmic trading; DLT (distributed ledger technology) comprises trade 
finance (smart contracts) and settlements including custody of crypto-assets and tokenisation of traditional financial instruments. The 
data are drawn from the ECB’s horizontal assessment of the survey on digital transformation and the use of fintech, conducted with all 
banks supervised by the ECB. 

Conclusion 

AI may bring benefits and risks at the financial institution level as well as for the 
entire financial system. The significant technological leap forward in the domain of 
AI may be a driver of economic progress that benefits consumers, businesses and the 
economy as a whole. AI can increase the efficiency of financial intermediation via 
faster and more comprehensive information processing that supports 
decision-making, which may strengthen the financial system and contribute to 
financial stability as well. At the same time, the technological challenges associated 
with AI limit its robustness and increase risks related to bias, hallucinations or misuse. 
These may distort financial market outcomes, impair the robustness of the operational 
framework or systematically bias information processing and institutions’ risk 
management or decision-making. 

The systemic implications of AI will depend on the levels of technological 
penetration and supplier concentration, which are difficult to predict. AI 
technology and its usage in the financial sector is still evolving. Furthermore, 
additional considerations, such as the broader macroeconomic and climate-related 
effects of AI as well as the moral and ethical aspects of the (mis-)use of AI, need to be 

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explored further. The latter could have an impact on public trust in financial 
intermediation, which is a cornerstone of financial stability. Therefore, the 
implementation of AI across the financial system needs to be closely monitored as the 
technology evolves. Additionally, regulatory initiatives may need to be considered if 
market failures become apparent that cannot be tackled by the current prudential 
framework.135 

Box A 
The implications of artificial intelligence for cyber risk: a blessing and a curse 

Prepared by Sándor Gardó, Benjamin Klaus, Luca Mingarelli and Jonas Wendelborn 

Cyber incidents can pose systemic threats to the financial system. Systemic events can arise if 
many institutions are affected at the same time (e.g. when a widely used program or service provider 
is involved) or an incident at one entity propagates to the broader system via financial, operational or 
confidence channels.136  As digitalisation progresses, potentially driven further by the rise of artificial 
intelligence (AI), additional layers of interdependence between financial firms, digital service 
providers and software vendors may emerge and may act as propagation channels for cyber 
incidents. As such, there has been a marked increase in the number of cyber incidents in recent years 
(Chart A, panel a), with the trend picking up beyond key events like the US elections in 2016 and 
2020 and the Russian invasion of Ukraine in 2022, which were likely associated with increased 
cyberattacks. This led to sizeable losses for the global economy and triggered a debate on the 
insurability of large-scale attacks and on system-wide safeguards.137 

AI tools have been met with growing public and investor interest, including in the context of 
cyber risk. The number of publicly available AI models has grown substantially since the launch of 
ChatGPT in November 2022 (Chart A, panel b). Most of these models specialise in text processing, 
but a growing number are also designed for audio or visual purposes. At the same time, concerns 
have grown that recent advances in this technology may not only yield productivity-enhancing 
benefits but may also be used by cyber attackers for malicious purposes, highlighting the need for 
enhanced cyber defences. These aspects are mirrored by both Google search trends and the stock 
market performance of related sectors (Chart A, panels b and c). 

135   See also in this context the EU’s Artificial Intelligence Act as a general legislative initiative to promote the 

uptake of AI and address the risks associated with certain uses of such systems. 

136   See, for example, the article entitled “Towards a framework for assessing systemic cyber risk”, Financial 

Stability Review, ECB, November 2022, and “Systemic cyber risk”, ESRB, February 2020. 

137   “Advancing macroprudential tools for cyber resilience”, ESRB, February 2023. 

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Chart A 
The advance of AI technology has sparked public and investor interest, including on its implications 
for cyber risk and cybersecurity 

a) Number of publicly disclosed 
cyberattacks over time 

b) Number of open-source AI 
models, by type, and Google 
searches for “Cyber attack and AI” 

c) Stock price developments for 
cybersecurity and AI firms vs the 
broader market 

(2014-23, total) 

(Jan. 2021-Apr. 2024; left-hand scale: thousands, 
right-hand scale: index) 

(6 Jan. 2017-3 May 2024, indices: 6 Jan. 2017 = 
100) 

Sources: University of Maryland CISSM Cyber Attacks Database, Google Trends, Hugging Face, Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel b: the number of open-source models uploaded to the Hugging Face platform. Open-source models without information on the model type have 
been excluded from this chart: as at April 2024 they accounted for 49% of all models. “Multimodal” refers to models which are capable of processing information 
from different modalities, including audio, images, videos and text. The Google Trends shown here are measured as the 12-month moving average of an index 
which takes the value 100 for the point of highest search interest for the term since 2004. Panel c: “Broad market” depicts the MSCI ACWI IMI, while 
“Cybersecurity firms” reflects the MSCI ACWI IMI Cyber Security Index. “Magnificent 7” comprises the stocks of Amazon, Apple, Alphabet, Nvidia, Meta, 
Microsoft and Tesla. This is used as a proxy for AI firms, as most of them are active in the AI field, while many firms specialised only in AI are not publicly traded. 

When it comes to the interplay between AI and cyber risks, AI tools will enhance the 
capabilities of threat actors while also benefiting cybersecurity. From a conceptual perspective, 
opportunities arise for cyber defence where AI can, for instance, be useful for analysing large 
amounts of security signals, allowing for the real-time monitoring of network activity (Figure A). 
Pattern recognition can spot unusual user behaviour, which helps to enhance threat detection. This 
could also help mitigate insider threats – risky user behaviour could be identified and sensitive 
information could be blocked from leaving a financial institution’s network. Ultimately, there is 
potential for automated responses and risk mitigation. AI-driven productivity gains for cyber 
defenders can also help mitigate a shortage of cybersecurity experts, generate cost savings and 
optimise cyber-defence strategies. Nonetheless, cyber threats could also rise as AI may enlarge the 
pool of potential cyber criminals as well as victims, while also improving the efficiency and 
effectiveness of underlying techniques. For instance, AI models could be used to research potential 
target systems and victims or help with coding.138  AI could help to significantly lower the entry barrier 
for would-be hackers or increase the effectiveness of professional hackers by finding vulnerabilities or 
helping evade detection. In addition, AI tools can be used as vehicles for an attack by manipulating 
the output they provide. AI tools with visual or audio output can be used to create deepfakes for social 
engineering attacks. 

138   See “Staying ahead of threat actors in the age of AI”, Microsoft Threat Intelligence, 14 February 2024. 

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Figure A 
Potential implications of AI for cyber risks 

Source: ECB. 

Phishing, among all types of cyberattack, seems particularly relevant for the financial 
industry and prone to enhancement with AI. As phishing139  attacks rely heavily on projecting 
authenticity and trust, AI has a particular potential to strengthen the attacks. First, it can enhance the 
persuasiveness of attackers, making them sound more convincing, not just by improving written text 
and making it more personalised, but also by employing deepfakes for voice- or video-based 
communication. Second, it can automate large-scale phishing campaigns, increasing their reach and 
effectiveness. In fact, detected phishing activity has grown considerably in the last couple of years 
(Chart B, panel a), coinciding with the broader availability of AI models. These attacks target a wide 
range of individuals, possibly with the ultimate objective of gaining elevated or privileged level access 
within financial institutions’ systems (privilege escalation attack). As at year-end 2023, over a fifth of 
all phishing activities targeted the financial sector, making it the second most affected industry after 
social media (Chart B, panel a). The ensuing interlinkages are crucial not only for the financial sector 
but also for other industries, as information gleaned from social media profiles can often be used to 
gain privileged level access within an individual’s place of employment. In addition, more widespread 
use of social media may also help spread rumours and disinformation faster, which could raise 
financial stability concerns to the extent that they trigger herding behaviour. 

139   Phishing is a form of social engineering attack that aims to gather sensitive information by impersonating 

trusted sources or individuals. This can happen in writing or by phone, or a combination of both. 

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Chart B 
Phishing activity has boomed in recent years, with both financial institutions and social media 
increasingly targeted, highlighting the need for enhanced cyber defences 

a) Total number of unique phishing websites (attacks) detected and 
sectoral breakdown 

b) Cyber Defense Index 2022/23 

(left graph: 2014-23, millions; right graph: 2020, 2023, share of total number of unique phishing websites 
(attacks) detected) 

(score from 0 (lowest) to 10 (highest)) 

Sources: APWG, MIT Technology Review and ECB calculations. 
Notes: Panel b: “Euro area” is an unweighted average of Germany, Spain, France, Italy and the Netherlands. SaaS stands for software as a service. The Cyber 
Defense Index ranks the world’s 20 largest economies according to their collective cybersecurity assets, organisational capabilities and policy stances. It 
measures the degree to which they have adopted technology practices that advance resilience to cyberattacks and how well governments and policy 
frameworks promote secure digital transactions. 

Looking ahead, the use of AI for both cyber defence and cyberattacks is expected to evolve 
over time. While AI tools in their current form may be particularly useful for creating more credible 
cyberattacks or exploiting deepfakes for social engineering, they could also be used to design new 
types of attack in the future. This highlights the need for cybersecurity professionals to exploit the 
benefits of technological advances such as AI to keep up with an ever-evolving cyber threat 
landscape and enhance cyber resilience. This is an area where, by international standards, at least 
some euro area countries appear to have room for improvement (Chart B, panel b). Dynamics in 
cybersecurity are essentially driven by an arms race between cyber defenders and threat actors – 
and AI is adding to the tools of both sides. It is currently difficult to assess who will gain the upper 
hand, and the momentum may well change over time. Nevertheless, given the potential for disruption 
if a systemic cyber incident occurs, it is important for financial institutions, as well as supervisors and 
regulators, to closely monitor associated developments. 

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C 

Private markets, public risk? Financial stability 
implications of alternative funding sources 

Prepared by Katharina Cera, Pierce Daly, Lieven Hermans, Philippe 
Molitor, Oscar Schwartz Blicke, Andrzej Sowiński and Elisa Telesca 

Euro area private markets have grown significantly in recent years, providing 
alternative funding sources for companies and diversification benefits for investors. 
While private markets are currently small relative to public markets and bank lending 
in the euro area, continued strong growth, financial innovation and opaqueness in 
private markets could contribute to financial stability risks. Adverse economic shocks 
could result in rising defaults, valuation corrections and losses for private funds and 
their investors. Additionally, such shocks may be exacerbated by multiple layers of 
leverage at company, fund and investor level, or by liquidity mismatches for some 
open-ended private funds. For banks, risks could arise from lending exposures to 
these markets, as well as from rising competition with private funds, which could 
incentivise lower underwriting and credit standards. 

Introduction 

Private markets have experienced remarkable growth in the euro area over 
recent years, bringing both benefits and risks for euro area financial stability. 
Private markets offer an alternative funding source to companies and real assets, next 
to public equity, corporate bond markets and bank lending. They fulfil an important 
economic function, as they match the financing needs of riskier economic entities with 
the risk-bearing capabilities of long-term investors. Their growth has been driven both 
by investors’ wishes for high returns, especially during the period of ultra-low interest 
rates, and by the need of companies for faster and more flexible sources of finance.140 
Despite their strong growth in recent years, private markets in the euro area remain 
relatively small compared with domestic public markets, bank balance sheets or global 
private markets. This special feature discusses the main developments in these 
markets since 2010, as well as risks to financial stability stemming from characteristics 
of investors, portfolio companies, the structure of intermediaries and links with the 
banking sector.141 

Overview of private market segments and strategies 

Private markets offer financing to companies through private equity and private 
credit, and for real assets (Figure C.1). Private market transactions are mainly 

140   Private credit may offer advantages over bank debt, such as higher leverage, a more flexible covenant 
structure and greater certainty and speed of execution; see Block, J., Jang, Y.S., Kaplan, S.N. and 
Schulze, A., “A Survey of Private Debt Funds”, Working Paper Series, No 30868, National Bureau of 
Economic Research, 2023. 

141   Financial stability considerations from the global private credit market have been discussed recently. 

See, for example, “Chapter 2: The Rise and Risks of Private Credit”, Global Financial Stability Report, 
International Monetary Fund, April 2024. 

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conducted via closed-ended funds (“private funds”). Private funds include private 
equity, private credit and real asset funds. Private equity funds invest into firms’ equity, 
while private credit funds lend to firms and real asset funds invest in assets such as 
property. These funds are typically accessible only to institutional investors, many of 
which have a long investment horizon.142  They also receive debt financing from banks 
(Figure C.1). When a private fund is set up, the investors commit capital which is 
typically called over the first years of the fund’s lifetime to finance investment 
opportunities.143  Accordingly, the assets under management of a private fund can be 
split into the net asset value (NAV) of the fund’s portfolio and its “dry powder” – 
committed, but not yet called capital. Depending on the fund type, investors either 
receive regular income streams from these investments or are paid out as the fund 
exits its individual investments or when it is liquidated at the termination date. Some 
funds, however, have indefinite lifespans (“evergreen” funds). Private markets are 
regulated relatively lightly, as most funds have limited liquidity mismatches or are 
closed-ended and focus on institutional investors.144 

Private equity strategies can be split by the stage of maturity of target 
companies and degree of equity investment. There are three main private equity 
strategies. First, venture capital funds typically hold minority equity stakes in young 
firms and engage operationally with their portfolio companies. Second, by contrast, 
leveraged buy-out (LBO) funds acquire controlling stakes in mature companies to 
raise their value by restructuring them and often also replacing their management. 
Such transactions are typically executed in the context of mergers and acquisitions. 
They involve a high degree of leverage in the form of syndicated loan financing 
arranged by banks or through private credit markets. Third, growth capital strategies 
are usually associated with taking a minority stake in the company, preferring to target 
mature businesses looking for capital to expand or restructure operations. Across all 
these strategies, private equity funds realise their returns mainly by selling a portfolio 
company to a strategic or financial buyer145  or by conducting an initial public offering. 

Private credit strategies differ in the seniority and purpose of lending and 
usually generate a constant revenue stream. The four most common strategies for 
funds located in the euro area are direct lending, mezzanine debt, special credit 
situations and distressed debt.146  In principle, direct lending is less risky, while other 

142   In some jurisdictions, private market products are also increasingly offered to high-net-worth and retail 

clients; see “Case study on private finance and non-bank financial intermediation”, Global Monitoring 
Report on Non-Bank Financial Intermediation 2023, Financial Stability Board, December 2023, pp. 
63-71. 

143   A private fund’s legal documentation specifies the timing and frequency of capital calls. A private fund 
manager commonly has the discretion to make capital calls based on an assessment of investment 
opportunities and capital requirements. Investors are expected to respect their capital commitments 
when the fund manager makes a capital call. While relatively rare, an investor default carries very serious 
implications, such as reduced ownership stakes or removal from the investment. 

144   For a more detailed discussion on the characteristics of private markets, see “The rise of private 

markets”, BIS Quarterly Review, Bank for International Settlements, December 2021. 

145   A strategic buyer is a buyer within the same industry as the portfolio company. A financial buyer is often 

another private equity firm. 

146   There is no consensus on what types of credit exposures should be included in the definition of private 
credit. Some only consider direct lending while others take a wider view, including any asset-backed 
structures. In addition, the private credit market can also encompass bridge financing, special situations, 
direct lending, distressed debt, infrastructure debt, mezzanine, real estate debt and venture debt. 

Financial Stability Review, May 2024 – Special Features 

121 

 
 
 
strategies are associated with higher probabilities of default. Until recently, private 
credit loans have commonly been provided to mid-sized (“middle market”) companies, 
featured floating interest rates and were neither rated nor broadly syndicated.147 
Private credit loans are not considered transferable securities and are not issued via 
public offers. They come with lower reporting requirements than (public) corporate 
bond markets, thus permitting more flexible and more rapid financing. More recently, 
however, some private credit funds have started bundling their debt into collateralised 
loan obligation (CLO) vehicles, which are sold to investors in tranches (Figure C.1). 

Figure C.1 
Private market funds channel funding from institutional investors to the real economy 

Source: ECB. 
Notes: PE stands for private equity; PC stands for private credit; CLO stands for collateralised loan obligation. Banks also lend to private 
credit and real asset funds through NAV lending, which is not shown in the chart. 

Some private equity and private credit funds are connected by ownership links 
and co-investments in the same portfolio companies. Most asset managers active 
in private markets have expanded their business from the equity space to credit, 
resulting in private equity and private credit funds often being managed by the same 
asset manager (Figure C.1).148  The growth in private credit funds is also related to 
such funds increasingly moving into the business of financing the debt required by 
private equity funds in LBO transactions, which had traditionally been financed by 

147   These are firms with revenues between USD 10 million and USD 1 billion; see Hancock, K., “What is 

middle market private equity”, PitchBook Data, Inc., March 2023. In this sense, private credit loans are 
distinct from leveraged loans or broadly syndicated loans, which are generally loans originated by a 
syndicate of banks to typically larger, highly indebted companies. 

148  According to Block, J. et al., op.cit., 40% of surveyed European private debt funds are affiliated with 

private equity firms. 

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122 

 
 
 
 
syndicates of investment banks. In 2023, 81% of European LBOs were financed by 
private credit, compared with 56% in 2021.149 

Real asset funds invest into real estate, infrastructure and natural resources via 
equity and debt instruments. While this special feature mainly focuses on the 
private equity and private credit subsegments, real assets are usually also considered 
a subsegment of private markets when investments are carried out via private 
transactions. This includes private real estate funds, which might be particularly 
vulnerable to the current downturn in the commercial real estate market.150 

Chart C.1 
Private markets remain concentrated in North America, but other jurisdictions have 
recently experienced significant growth 

Private market funds’ assets under management, by fund location and fund type 

(Q4 2010, Q4 2020, Q3 2023; left-hand scale: € trillions, right-hand scale: percentages) 

Sources: PitchBook Data, Inc. and ECB calculations. 
Notes: Private equity includes venture capital funds. Fund location is defined as where the fund management team is located. The red 
line shows the compound annual growth rate of assets under management between Q4 2010 and Q3 2023 for funds split by location and 
fund type. Real asset funds comprise funds investing into real estate, infrastructure and natural resources. 

Although private market funds remain concentrated in the private equity 
segment and in North America, other segments and locations have grown 
significantly over recent years. In the third quarter of 2023, the lion’s share of assets 
under management in private funds was held by funds located in North America. 
Private equity funds remain the largest asset class, accounting for 68% of global 
assets under management in private funds, followed by real asset funds at 20% and 
private credit at 12%. While assets under management in private funds located in the 
euro area are still small compared with funds investing in public markets,151  they have 

149   See Q4 2023 European Credit Markets Quarterly Wrap, PitchBook Data, Inc., January 2024. 
150   Real estate funds are important actors in the euro area commercial real estate (CRE) market and are 
sometimes owned by private equity firms. Their growing market footprint makes them vulnerable to a 
CRE market downturn, especially in the case of open-ended funds with structural mismatches between 
asset liquidity and redemption terms. See the article entitled “The growing role of investment funds in 
euro area real estate markets: risks and policy considerations”, Macroprudential Bulletin, ECB, April 
2023. 

151   As of the third quarter of 2023, assets under management of euro area private market funds stand at 
€960 billion, or 6% of the euro area investment fund sector’s total assets (source: ECB IVF statistics). 

Financial Stability Review, May 2024 – Special Features 

123 

 
 
 
 
seen steep growth over the last decade. Compound annual growth rates stand at 14% 
for private credit funds, 12% for real asset funds and 10% for private equity funds 
(Chart C.1).152 

Benefits and risks for financial stability 

Private markets provide benefits to the economy. They offer an alternative source 
of funding, with often faster and more reliable execution. For investors, they provide a 
portfolio diversification option and constant income streams. For the wider economy, 
private markets often finance the kind of smaller, riskier and innovative firms that are 
important for future economic growth. In particular, the equity segment of private 
markets − venture capital, for instance − could play an important role in funding the 
innovation that is essential for the green and digital transitions.153  In this respect, 
growth in euro area private markets can also support the development of the capital 
markets union in the euro area. 

Nonetheless, the opaqueness and strong growth of private markets may give 
rise to financial stability risks. This special feature later assesses some potential 
contagion channels by reviewing the characteristics of investors into private markets, 
portfolio companies, the structure of fund intermediaries, and links between private 
markets and the banking sector. 

Large institutional investors tend to be the main investors in private funds. 
Globally, insurance corporations and pension funds (ICPFs) account for close to 75% 
of investments into private equity funds and around 86% into private credit funds.154 
Focusing on entities domiciled in the euro area, the latest available data indicate that 
occupational pension funds had invested around 4% of their total assets into private 
equity funds and 2% into infrastructure funds in the third quarter of 2023, while 
exposures to private credit were likely substantially lower. Insurers had even smaller 
exposures to private equity, private credit and infrastructure funds, but they had a 
more substantial share of direct loans on their balance sheets (Chart C.2, panel a). 
While the general move of ICPFs into illiquid assets – including private funds – was to 
some extent driven by their search for yield during the period of ultra-low interest rates, 
they represent the financial sector with the highest capacity to hold illiquid exposures, 
given their very long-term investment horizons. ICPFs also seem well prepared for 
managing the liquidity needed to meet the capital calls that are a characteristic of 
private market investments. 

152   While the European private credit segment in particular is somewhat concentrated in the United 

Kingdom, growth in private credit funds in the EU may be supported by the Alternative Investment Fund 
Managers Directive (AIFMD) II, which establishes common rules for loan-originating alternative 
investment funds. 

153   See in particular the box entitled “Making euro area equity markets fit for green and digital innovation”, 

Financial Integration and Structure in the Euro Area, ECB, April 2022. 

154   See Graph 3 in “The rise of private markets”, BIS Quarterly Review, Bank for International Settlements, 

December 2021. 

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124 

 
 
 
Chart C.2 
Uncertainty in private asset valuations might hide losses for institutional investors, 
who could nonetheless also profit from lower volatility 

a) Share of alternative assets in total assets 
held by euro area insurance corporations and 
pension funds 

b) Performance of euro area-located private 
credit funds vs public debt indices 

(Q4 2020, Q3 2023, percentages) 

(Q1 2020-Q1 2024; indices, 2 Jan. 2020 = 100) 

Sources: EIOPA, Bloomberg Finance L.P., PitchBook Data, Inc. and ECB calculations. 
Notes: Panel a: pension funds include only occupational pension funds. Real estate includes direct holdings of real estate (i.e. physical 
property) and indirect holdings (i.e. real estate fund and company shares, securities and mortgages). Direct loans exclude mortgages. 
Other alternative funds are alternative funds as categorised by EIOPA, which also includes private credit funds. Panel b: the performance 
of private credit funds is calculated as quarterly compounded median internal rates of return. The European leveraged loan index 
corresponds to the Morningstar European Leveraged Loan TR EUR Index. The euro high-yield bond index corresponds to the ICE BofA 
Euro High Yield Index. All indices are indexed to 100 as of 2 January 2020. 

Despite banks’ limited direct investments into private funds, risks might spill 
over from private markets via their lending exposures and incentives to lower 
credit standards. In addition to common exposures to companies which are financed 
by banks and private markets, banks also lend to private funds and fund investors. 
These loans are usually collateralised by the funds’ NAV (“NAV lending”) or, in the 
case of lending to private funds, also by the funds’ dry powder. Private funds might use 
the additional funding from banks to support their portfolio companies, lever up returns 
or pay out their investors in a challenging exit environment like the current one.155  The 
credit risk from such bank exposures seems contained in both cases, however. First, 
typical loan-to-value ratios in NAV lending range between only 10% and 15%.156 
Second, market intelligence suggests that the risk of investors defaulting on capital 
calls, thus undermining the value of loan collateral, is rather small, as the contractual 
obligation to deliver the capital is strong. Nevertheless, aside from lending exposures, 
growing private credit markets are increasingly competing with banks’ syndicated 

155   Various reports point to a slowdown in exit activity attributable to less deal-making amid tighter financing 
conditions, which has led to a decrease in distributions to investors (see, for example, 2024 Allocator 
Outlook, PitchBook Data, Inc., December 2023). Some sources point at NAV loan proceeds being used 
mainly for distributions − a debatable practice − while others estimate this use at only 8% of proceeds; 
see Case study on private finance and non-bank financial intermediation”, Global Monitoring Report on 
Non-Bank Financial Intermediation 2023, Financial Stability Board, December 2023, and “Is NAV 
Lending Good or Bad for GPs and LPs?”, Crestline Investors, Inc., October 2023. 

156   See “NAVigating Considerations and Controversies Around NAV Loans”, PitchBook Data, Inc., 

December 2023. 

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125 

 
 
 
 
 
lending activities. This, in turn, might incentivise banks to lower their lending standards 
to protect their market share. 

Valuation methods in private markets may disguise potential losses. The nature 
of holdings in private funds makes it challenging to mark these types of assets to 
market. In turn, private funds’ assets are valued less frequently and under more 
subjective model assumptions, which can conceal potential losses, underlying 
volatility and the correlation between the returns on private funds with other markets. 
This can lead to cliff-edge losses for institutional investors if private funds only 
recognise write-downs at the end of individual investments. At the same time, lower 
reported volatility artificially boosts risk-adjusted returns and might help some 
investors meet their internal or regulatory risk limits, another incentive for investing 
into these markets. Compared with high-yield bonds and leveraged loans, median 
returns on private credit funds did not suffer losses during the pandemic stress period 
or since the start of the monetary policy tightening cycle (Chart C.2, panel b). 

Chart C.3 
Private credit is provided to relatively stronger euro area companies than private 
equity 

a) Private credit volume, by euro area 
borrower sector and geographical distribution 
of lenders 

b) Median interest coverage ratio for private 
equity and private credit-backed firms, and 
firms in public equity and bond indices 

(2019-23; left-hand scale: € billions, right-hand scale: percentages)  (Q2 2023, EBITDA/interest expenses) 

Sources: PitchBook Data, Inc., Bloomberg Finance L.P. and ECB calculations. 
Notes: Panel a: sector volume is calculated as the aggregated lending to each sector in 2019-23. Geographical distribution refers to the 
share of total lending in 2019-23, broken down by lender location. In a debt with several loan underwriters with different geographies, the 
debt volume is divided evenly between lenders. This is done to avoid double-counting private credit volume in geographical distribution. 
B2B refers to business products and services; B2C refers to consumer products and services. Panel b: ICR stands for interest coverage 
ratio; HY stands for high-yield debt; IG stands for investment-grade debt. The ICR of euro public HY is based on median ICRs of 
companies with bonds in the ICE BofA Euro High Yield Index. The ICR of euro public IG is based on companies with bonds in the ICE 
BofA Euro Corporate Index. Euro area private equity ICR is based on a sample of 7,093 euro area firms, while euro area private credit 
ICR is based on 388 euro area firms. Most private credit-backed firms are also publicly listed, but there is little overlap between private 
credit and private equity-backed companies in the sample considered. The sample includes firms with any available ICRs between Q2 
2022 and Q2 2023. 

Private lending to euro area companies mainly comes from non-euro area 
private credit funds and seems concentrated in more innovative sectors. 
Cross-border lending is an inherent feature of private credit markets, with only around 
20% of the volume borrowed by euro area companies being lent by euro area 

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126 

 
 
 
 
borrowers (Chart C.3, panel a). While private credit funds used to focus on lending to 
smaller and riskier companies, market intelligence suggests that, in recent years, they 
have moved further up the credit quality spectrum and into larger deals. According to 
data from PitchBook covering a sample of 258 deals, median private credit deals in the 
euro area increased from €75 million in 2021 to €168 million in 2023. In addition, 
private credit funding seems concentrated in more innovative sectors, such as 
business products and services, health care and information technology. 

Companies backed by private credit do not seem to have worse credit quality 
than their public peers. Based on available data, on average, private credit-backed 
companies do not appear to have lower interest coverage ratios – which indicates the 
extent to which earnings cover interest expenses − than their exclusively public 
debt-financed peers (Chart C.3, panel b). Importantly, this may suggest that the 
comparative advantage of private lenders is the greater flexibility and speed of 
execution rather than their ability to offer funding to riskier borrowers. Additionally, the 
use of “amend and extend” agreements might prevent defaults from materialising, 
although it might also add to the risk of delayed recognition of losses for funds and 
their investors.157 

By contrast, private equity-backed companies tend to display worse credit 
quality than their public peers, which raises financial stability concerns. While 
interest coverage ratios of publicly listed companies average around 13.8 – i.e. on 
average, their earnings cover almost 14 times their interest expenses on their 
outstanding debt – those of private equity-backed companies are significantly lower, at 
1.6 on average (Chart C.3, panel b). This is likely due to LBO strategies which lever up 
funds’ portfolio companies, enhancing investor returns. Higher leverage is also 
connected with higher probabilities of default and lower recovery rates. These 
vulnerabilities are more likely to materialise in an environment of slow growth and 
might bring material losses to lenders, including banks and private credit funds. 
Private equity firms might also have fewer incentives to support struggling companies 
than strategic investors.158  On a positive note, globally, private equity funds currently 
have €2.3 trillion of dry powder available, which gives them room to act 
countercyclically. 

A sizeable share of euro area private credit funds are open-ended funds, which 
may raise liquidity risks. In contrast to private equity funds, which are primarily 
closed-ended,159  approximately 42% of private credit funds have an open-ended 
structure. Of these funds, most are domiciled in France and Luxembourg (Chart C.4, 
panel a). Although an open-ended fund structure may help attract investors,160  it may 
also highlight potential liquidity mismatches between the illiquid nature of funds’ 

157   According to PitchBook, 16% of newly originated private credit loans to euro area borrowers in 2023 were 
attributed to debt refinancing, up from 0% in 2022. This implies that private credit funds might enable 
firms to refinance and extend loans. 

158   For further details, see, for example, the box entitled “Financial stability implications of private equity”, 

Financial Stability Review, ECB, May 2020. 

159   See “EU Alternative Investment Funds 2023”, ESMA Market Report, European Securities and Markets 

Authority, January 2024. 

160   See, for example, Mounguia, M.-L. and Dubar, J., Private Debt – An Expected But Uncertain “Golden 

Moment”?, Ernst & Young, 8 January 2024. 

Financial Stability Review, May 2024 – Special Features 

127 

 
 
 
assets and their redemption terms. Such vulnerabilities may nonetheless be mitigated, 
depending on funds’ redemption frequency, presence of lock-in periods and 
availability of liquidity management tools (e.g. redemption gates and temporary 
suspensions). In addition, the role of ICPFs as main investors may limit liquidity risks 
for such funds, thanks to their long investment horizons (Chart C.2, panel a). 

Chart C.4 
Open-ended private credit funds may be exposed to liquidity mismatches, while euro 
area holdings of private credit CLOs remain low 

a) Share of closed- and 
open-ended euro area private 
credit funds, by domicile 

b) Global CLOs outstanding, 
by issuer area and type 

c) Capital structure and share 
of senior loans of US CLOs, by 
type   

(Q3 2023, percentages) 

(Jan. 2014-Mar. 2024; left-hand scale: 
€ trillions, right-hand scale: percentages) 

(Jan. 2011-Mar. 2024, percentages) 

Sources: PitchBook Data, Inc., ECB (investment fund list, SHS, CSDB) and ECB calculations. 
Notes: EA stands for euro area; CLO stands for collateralised loan obligation; BSL stands for broadly syndicated loan; PC stands for 
private credit. Panel a: the sample of funds is calculated based on euro area private credit funds identified by PitchBook as well as funds 
with “private credit”, “middle market”, “direct lending” and “loan origination” in their name as shown in the ECB’s list of investment funds. 
The chart excludes approximately 5% of funds that do not report whether they are closed- or open-ended. Panel b: the euro area 
holdings of CLOs are identified by matching CLO issuer names from PitchBook to SHS data. The two lines show the total euro area 
sectoral CLO holdings as a share of total CLO amount outstanding, by type. Panel c: the bars depict the tranches’ aggregate shares of 
the total historical issuance of US BSL and private credit CLOs between January 2011 and March 2024. The dots represent the average 
share of senior secured loans within each CLO portfolio, weighted by the respective CLO size for the total BSL and private credit US CLO 
historical issuance. 

Private credit CLOs are on the rise, although so far solely in the US market and 
with little exposure to euro area holders. Private credit CLOs – securities that are 
backed by a pool of private loans and divided into tranches with varying credit quality – 
have been growing rapidly in recent years. At the beginning of 2024, they accounted 
for 11% of all outstanding US CLOs (Chart C.4, panel b). While this segment is so far 
only present in the US market and exposures of euro area holders are negligible, 
some market observers expect a pick-up in Europe in the course of 2024.161  Private 

161   See, for example, Rae, M., “2024 European CLO Outlook: Steady state, with private credit on horizon”, 
PitchBook Data, Inc., December 2023; Rae, M., “Middle market CLOs only a matter of time for Europe, 
managers say”, PitchBook Data, Inc., November 2023; Thiele, V., “Stop dreaming of private credit CLOs, 
the arb is enough of a nightmare”, GlobalCapital, October 2023; and Tipping, N., “Why Europe still awaits 
a private credit CLO”, Risk.net, April 2024 

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credit CLOs typically have a larger equity tranche and a slightly smaller AAA tranche 
than traditional, or broadly syndicated loan, CLOs (Chart C.4, panel c), which may 
signal higher credit risk.162  Moreover, unlike in traditional CLOs, private credit CLO 
issuers often retain the entirety of the equity tranche, which along with the tranche’s 
larger size, increases exposures to future potential losses. However, private credit 
CLOs typically have a slightly higher share of senior secured loans than their 
traditional peers,163  as well as a significantly lower share of covenant-lite loans.164  A 
covenant-heavy portfolio could nonetheless also increase the effective credit risk 
under some circumstances, as more stringent conditions applied to loans included in 
the CLO might increase the probability of default. In light of these considerations, it 
would be important to also monitor the resilience of a future private credit CLO market 
in Europe, were this to emerge. 

Private markets still need to prove their resilience in an environment of higher 
interest rates as they have grown to a significant size only in the past decade. 
Higher interest rates might affect private markets through two channels. First, higher 
discount rates reduce the fundamental value of assets (affecting all private funds) and 
increase default risk in private credit portfolios, especially when interplaying with 
slowing growth. Losses might remain hidden until maturity or the exit from the 
investment due to the lack of marking to market. Second, it remains to be seen to what 
extent higher returns on safe assets will slow investor demand for alternative assets. 
The relatively high level of dry powder in private funds is a mitigating factor. 

While financial stability risks from private markets seem contained in the euro 
area, some concerns remain. Aggregated exposures, opaqueness and private 
markets’ resilience are all elements that warrant monitoring, especially in an 
environment of higher interest rates. Given the limited liquidity mismatches of private 
funds in aggregate, and the long-term investment horizons of their main investors, 
risks to euro area financial stability from private markets appear limited. Still, it is 
conceivable that while the aggregate picture seems benign, risks may lurk in 
concentrated exposures. It is important to continue monitoring developments in 
private markets, including newer trends like the increase in private credit CLOs and 
NAV lending, and potential challenges from higher interest rates. However, monitoring 
remains hampered by opaqueness and data scarcity. This makes it all the more 
important to improve transparency concerning private markets. 

162   In CLOs, the equity tranche is at the bottom of the priority ladder and has the highest risk and potential for 
return. Equity investors are the last to receive payments and the first to absorb any losses from defaults in 
the loan pool. However, if the performance of the first lien loans is strong, equity tranches can realise 
significant returns after all other tranches have been paid. After the senior and mezzanine tranches have 
been satisfied, the cash flows from first lien loans flow to the equity tranche. 

163   Senior secured loans, or first lien loans, are secured by the borrower’s assets and by a first-priority claim 
on the collateral of the borrower. This means that in the event of liquidation, the proceeds from the sale of 
the collateral must first be used to repay these loans before subordinate loans. 

164   According to PitchBook and ECB calculations, the average share of covenant-lite loans, defined as loans 
which have fewer or less stringent covenants than traditional loans, within US traditional CLOs weighted 
on their total historical issuance decreased from 70% to 60% between 2019 and 2023. At the same time, 
the share for US private credit CLOs increased from 10% to 20%. 

Financial Stability Review, May 2024 – Special Features 

129 

 
 
 
 
Acknowledgements 

The Financial Stability Review assesses the sources of risks to and vulnerabilities in the euro area financial system based on regular 
surveillance activities, analysis and findings from discussions with market participants and academic researchers. 

The preparation of the Review was coordinated by the ECB’s Directorate General Macroprudential Policy and Financial Stability. The 
Review has benefited from input, comments and suggestions from other business areas across the ECB. Comments from members of the 
ESCB Financial Stability Committee are gratefully acknowledged. 

The Review was endorsed by the ECB’s Governing Council on 8 May 2024. 

Its contents were prepared by Desislava Andreeva, Paul Bochmann, Pierce Daly, Daniel Dieckelmann, John Fell, Sándor Gardó, Lucyna 
Górnicka, Paul Hiebert, Annalaura Ianiro, Thore Kockerols, Mara Pirovano, Linda Rousová, Andrzej Sowiński, Manuela Storz and Jonas 
Wendelborn. 

With additional contributions from Lorenzo Cappiello, Johanne Evrard, Alessandro Ferrante, Maciej Grodzicki, Lieven Hermans, Barbara 
Jarmulska, Benjamin Klaus, Georgi Krustev, Caterina Negri, Charles O'Donnell, Valerio Passantino, Cristian Perales, Allegra Pietsch, 
Petya Radulova, Moreno Roma, Ellen Ryan, Oscar Schwartz Blicke, Emilio Siciliano, Elisa Telesca, Michael Wedow, Christian Weistroffer, 
Regine Wölfinger, Stefan Wredenborg and Balázs Zsámboki. 

Editorial, multimedia and production assistance was provided by Paula González Escribano, Anna Heckler, Peter Nicholson, Katie Ranger 
and Verena Reith. 

© European Central Bank, 2024 

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