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Strengthening risk monitoring and policy for non-bank leverage

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

Published as part of the Macroprudential Bulletin 15, January 2025.

Leverage in the non-bank financial intermediation (NBFI) sector can be a source of systemic risk and amplify stress in the wider financial system. Policymakers are currently considering ways to address NBFI leverage risks, with the focus on containing the build-up of such risks ex ante. To achieve this, authorities need a broad toolkit that allows them first to identify leverage risks and then to address them. Taking advantage of recent improvements in data availability, this edition of the Macroprudential Bulletin explores novel approaches to identifying risks and designing policies. In doing so, it contributes to the wider ongoing debate on addressing risks from NBFI leverage.

1 Introduction

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. The NBFI ecosystem comprises a wide range of entities performing different economic functions. This includes significant differences across entities in the level of leverage as well as the complexity in how leverage is obtained and used. Excessive leverage in the NBFI sector can make procyclical deleveraging and material counterparty losses more likely, 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 that of liability-driven investment funds in UK gilt market stress in September 2022.[1] Both episodes reveal how NBFI vulnerabilities related to 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 derivatives positions, combined with a lack of transparency on these positions, can impose significant counterparty losses on systemically important banks.[2] In some cases, extraordinary policy responses by public authorities and central banks were needed to stabilise markets and limit contagion. 

Authorities around the world have engaged in a wide range of policy initiatives to address risks posed by NBFI leverage.[3] At the domestic level, authorities have recently introduced a range of measures aiming to address leverage risks. These include activity-based measures, such as clearing mandates, and entity-based measures, such as leverage limits. A key finding from these recent policy initiatives is that no single tool can be uniformly used to address risks stemming from NBFI leverage. An effective policy response requires a broad range of tools that can be tailored to the specific vulnerabilities identified. It also requires an understanding of how these tools can complement each other. The Financial Stability Board (FSB) is currently developing recommendations to address the risks arising from NBFI leverage, including ex ante measures which would restrict the build-up of excessive leverage.[4]

2 Risk assessment and policy evaluation for non-bank leverage

For a policy framework to effectively address risks stemming from NBFI leverage, authorities must be able to measure and identify these risks. The global financial crisis highlighted significant vulnerabilities in both derivatives (synthetic leverage) and repo (financial leverage) markets that can spill over to broader financial markets. Since then, the activity-level data available to authorities on derivatives and securities financing transactions (including repos) has been greatly enhanced.[5] By providing comprehensive information on daily transactions, activity-level data help authorities obtain more timely and comprehensive insights into these markets, helping them to develop policy responses that address financial stability risks. However, to measure and identify leverage risks appropriately, authorities also need to have in place a robust risk assessment framework. The analyses in this edition of the Macroprudential Bulletin use a range of datasets and employ novel methodologies for measuring leverage risks.

The NBFI sector is playing an increasingly important role in euro area repo markets, so emerging risks need to be closely monitored, and potential policy responses evaluated. Recent episodes of stress in core government bond markets highlighted the use of repos by investment funds to build up leverage. As investment funds become increasingly relevant in the financial sector more generally, it is important to gain a better understanding of how much financial leverage funds take on via securities financing transactions (see Box 2). Given the increasing role of investment funds (e.g. hedge funds) in euro area repo markets, it is important to assess whether their activity could be a source of systemic stress in these markets (see Box 1). The choice of potential policy measures requires careful consideration of the circumstances, such as the type of activity and entity involved. In addition, in choosing which measures to take, policymakers must ensure that the resulting actions do not impose disproportionate costs, which could for example negatively affect liquidity and pricing in underlying markets or hedging incentives.

Synthetic leverage is a key source of vulnerability for the NBFI sector, yet measuring it remains a challenge. NBFI entities can also accumulate leverage via derivatives contracts. This is usually referred to as synthetic leverage. However, it can be difficult for authorities to measure, which can be due to lack of conceptual agreement as well as to data limitations. As a result, common leverage metrics on synthetic leverage may not adequately account for risk factors. Given the systemic importance of derivatives classes such as interest rate swaps, new approaches for measuring synthetic leverage are needed to support authorities in their scenario analysis and to help them investigate liquidity and solvency risk at the entity level (see Article 3).

An effective policy response also requires the implementation of previously agreed international standards to address leverage risks. An important interim step would be to adopt the FSB minimum haircut framework for securities financing transactions.[6] This would help in managing leverage in the NBFI sector generated from securities lending and repo transactions backed by non-government debt collateral. Evidence for the euro area shows that introducing the FSB minimum haircut framework for NBFI would lead to a sizeable reduction in leverage and could be an important measure for helping to contain the build-up of leverage from an ex ante perspective (see Article 4). This underscores the need to make progress on introducing this framework.

A thorough assessment of the design of entity-based and activity-based measures is crucial for understanding how effective they are in containing leverage-related risks. Combining entity-level and activity-level data allows authorities to better understand the use of NBFI leverage and assess its implications for financial stability (see Article 2). By merging entity-level data from the Alternative Investment Fund Managers Directive (AIFMD)[7] with transaction-level data for derivatives and SFTs, a clearer picture of the risks posed by leveraged investment funds can be presented. This allows authorities to develop a framework for flexibly analysing a range of risk scenarios. It also means they can evaluate regulatory measures in terms of both their effectiveness and their complementarity in addressing potential vulnerabilities arising from leverage.

A comprehensive approach to addressing NBFI risks also involves considering the role of lenders, including their risk management practices. The collapse of Archegos Capital Management in 2021 and the consequent spillovers to the banking sector raised questions about banks’ counterparty credit risk (CCR) management practices.[8] The use of supervisory banking data allows authorities to measure the CCR faced by banks, including from the NBFI sector. The use of stress test techniques can help to (i) quantify the level of systemic risk in a network of CCR exposures and (ii) determine how widely hypothetical defaults among more vulnerable NBFI counterparties can spread across the banking system. From a policy perspective, this gives authorities an indication of the kind of policy measures that may be effective in mitigating the risk of exposure to vulnerable NBFI entities (see Article 5).

3 Conclusion

The analyses presented in this edition of the Macroprudential Bulletin highlight the need for authorities to have an effective monitoring and policy framework to address NBFI leverage risks. NBFI leverage creates and augments complexities in an interconnected financial system. Authorities need a comprehensive policy toolkit to effectively address NBFI leverage risks for an effective policy response, which should be appropriately tailored to the specific vulnerabilities within their jurisdiction. Given the significant cross-border and cross-sector nature of these risks, close coordination and cooperation between various authorities is essential, ensuring that risks are addressed system-wide.

References

Avalos, F. and Sushko, V. (2023), “Margin leverage and vulnerabilities in US Treasury futures”, BIS Quarterly Review, Bank for International Settlements, September 2023.

Basel Committee on Banking Supervision (2024), “Guidelines for counterparty credit risk management”, December.

European Central Bank (2024), “Containing risks from leverage in the NBFI sector – insights from recent policy initiatives”, Financial Stability Review, ECB, May.

Financial Stability Board (2015), “Transforming Shadow Banking into Resilient Market-based Finance”, November

Financial Stability Board (2024), “Leverage in Non-Bank Financial Intermediation: Consultation report”, December

Financial Stability Board (2023), “The Financial Stability Implications of Leverage in Non-Bank Financial Intermediation”, September

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