2025 CCP Stress Test: results report

1: Foreword

Central counterparties (CCPs) are at the core of UK and global financial systems. By standing between buyers and sellers in financial transactions, they reduce counterparty credit risk and enhance market resilience. Their resilience in stress is a critical element in maintaining global financial stability.

The Bank of England’s (the Bank’s) regular stress testing of CCPs aims to identify any potential vulnerabilities and gaps in their financial resilience, with the findings used to inform the Bank’s ongoing supervision of CCPs.

This year’s CCP Stress Test is the fourth such test. It focuses on exploring CCPs’ resilience to an extreme but plausible stress scenario involving high levels of market volatility, consistent with rising geopolitical tensions, global fragmentation of trade and financial markets, and rising pressure on sovereign debt globally.

The results of the test are encouraging. They confirm that, in this scenario, UK CCPs would have sufficient pre-funded resources to absorb the default of the two members to which they have the largest exposures, thereby limiting contagion to the wider financial system and continuing to support the smooth functioning of core financial markets.

This year’s exercise includes exploratory internal analysis of CCP resilience against a much larger set of scenarios developed by the Bank. These include potential breakdowns in historical correlations and market moves which are beyond historical worsts, again with encouraging results. This work will be embedded into our ongoing supervision of UK CCPs to help us explore areas of potential vulnerability, assess resilience against emerging risks in real time, and inform our ongoing engagement with the CCPs.

The Bank’s work to explore the resilience of CCPs is useful for all their users. I hope they find this report valuable.

Sarah Breeden, Deputy Governor Financial Stability

2: Executive summary

Purpose and methodology

UK CCPs are central to the global financial system and are supervised by the Bank because of their importance to the smooth functioning of financial markets and the wider economy. As part of this supervision, the Bank conducts regular stress testing of UK CCPs. This report sets out the results of the Bank’s fourth public stress test of UK CCPs.

The 2025 CCP Stress Test focuses on the credit resilience of the Clearing Services at the three UK CCPs (ICE Clear Europe Limited (ICEU), LCH Limited (LCH), and LME Clear Limited (LMEC)), and whether they have resources to withstand severe market shocks and the default of two or more members, under a range of different assumptions. It aims to identify any potential vulnerabilities and gaps in CCPs’ financial resilience, with the findings used to support and inform the Bank’s supervisory and regulatory activities.

The Credit Stress Test assesses whether UK CCPs have sufficient resources to manage the losses of any two members under an extreme but plausible baseline Market Stress Scenario, specified by the Bank. This scenario explores similar risks as that of the Bank’s stress test of UK Banks and focuses on specific risks – rising geopolitical tensions, increased concerns around global fragmentation and rising pressure on sovereign debts – all of which create the conditions for a global slowdown.

Alongside the baseline scenario, we include additional ‘multiplier scenarios’ to explore resilience to more extreme scenarios, beyond historical precedents and regulatory requirements. This year’s exercise also includes desk-based analysis of a wider range of scenarios, including shocks that break historical correlations. This enables us to identify potential vulnerabilities or risks to a CCP’s financial resilience that may not be captured by the baseline scenario.

Similar to last year, this year’s exercise does not include a full liquidity stress test. Instead, we explored liquidity risks in a more qualitative manner, distributing a survey to each CCP. The responses, as well as information gathered from the Bank’s ongoing supervisory work in this area, are used to assess how liquidity risks have evolved since the 2023 stress test and reach a judgment on CCPs’ current liquidity resilience.

Results

In the core Credit Stress Test, which does not include the incremental costs of liquidating concentrated positions, we find that all UK CCPs have adequate pre-funded resources to cover a severe stress scenario which includes the default of the ‘Cover-2’ members – the two members whose default generates the greatest depletion of mutualised resources at the CCP.

The impact on CCP resources this year is lower than observed in 2024, but overall higher than in 2023. Our assessment is that the difference in outcomes compared to 2024 reflects the shape of the scenario, which this year is generally more broad-based across products, whereas last year’s scenario included shocks to some key products that went beyond historical worsts. The scenarios applied in 2023 and 2025 are more directly comparable and we attribute the greater use of mutualised resources in this stress test to the fact that CCP resources have adjusted to a period of less volatile market conditions, having been elevated in 2023. This is to be expected, given that the stress events of 2022 were then more heavily weighted in CCPs’ margin models.

When the additional costs of liquidating concentrated positions are added, we see that CCPs are still able to absorb these additional losses within pre-funded resources. The impact is greater at ICEU and LMEC, which operate in markets – namely metals and energy markets – which are potentially more susceptible to the build-up of concentrated and so less liquid positions.

This year’s exercise also includes exploratory internal analysis of CCP resilience against a much larger set of scenarios developed by the Bank. Whereas the core Credit Stress Test gives us deep insight into the impact of a specific scenario, this work considers a larger set of extreme but plausible scenarios. We use an internal stress-testing model to assess resilience against Cover-2 defaults under ~1,000 scenarios, selected as the most severe from an initial set of 50,000 drawn from a multivariate distribution fitted to historical data. We find that only a small fraction of these scenarios lead to use of non-defaulter resources and fewer than 10 exhaust the pre-funded resources held at any UK CCP. These scenarios tend to sit well beyond historical worsts, so this analysis gives us confidence that CCPs’ resources are sized appropriately.

The Bank will use the findings from the 2025 CCP Stress Test to support and inform its ongoing supervision and regulation of UK CCPs. We plan to follow up with the three CCPs in scope to share and discuss the results and pockets of risk identified. We will also share relevant results with other regulators and authorities. Beyond this, we plan to build on the internal modelling done this year and will not be conducting a full public stress test of UK CCPs in 2026. We will focus on further developing our internal stress-testing tools to conduct more dynamic and efficient testing of a wider range of risks and scenarios. The next public exercise will take place in 2027.

3: Introduction

As part of the Bank’s ongoing supervision of UK CCPs, we regularly conduct stress tests with the aim of identifying potential vulnerabilities and risks to CCP financial resilience. The 2025 stress test – the fourth public exercise – is exploratory in nature and focuses on the credit resilience of the three UK CCPs against a single Market Stress Scenario. We also use an exploratory internal stress-test model^{footnote [1]} to estimate the impact of a wider range of scenarios and to explore how CCP resources and resilience have evolved over the years the Bank has been running the exercise.

As in previous years, the stress test is not a pass-fail exercise. Nor is it aimed at checking compliance with regulations or assessing the quality of CCPs’ internal stress testing. Rather, it aims to identify any potential vulnerabilities and gaps in CCPs’ financial resilience, with the findings used to support and inform the Bank’s supervisory and regulatory activities.

The 2025 core stress test includes:

• Credit Stress Test: This explores CCP resilience to an extreme but plausible Market Stress Scenario (Section 4) and the default of the two member groups whose default generates the greatest mutualised losses at the CCP (a Cover-2 default). We have also complemented our analysis with comparisons over time using data provided by CCPs in previous exercises and our internal stress-test models.
• Credit and Concentration Stress Test: We extend the analysis to include the modelled costs of liquidating concentrated positions held by the defaulting clearing members, which may incur additional costs in a stressed market.
• Extensions and sensitivity testing: We also consider the impact of increasing the severity of the scenario and changing assumptions, including the number of defaulters and parameters for calculating concentration costs. This analysis intentionally leverages scenarios which go beyond historical precedents and regulatory requirements with the aim of identifying potential vulnerabilities and testing the frontiers of CCP resilience.
• Liquidity impacts: The 2025 CCP Stress Test does not include a full liquidity stress test, rather we used a qualitative questionnaire to identify how potential risks to CCP liquidity may have evolved since the 2023 exercise, which was when we last conducted a full Liquidity Stress Test. We also explore the liquidity impacts on CCPs’ members and clients.

All UK CCPs and relevant Clearing Services are in scope, summarised in Table A.

4: Market Stress Scenario

Market Stress Scenario

The 2025 CCP Stress Test is centred on a hypothetical Market Stress Scenario developed by the Bank. This scenario includes escalating concerns about global fragmentation, represented by reduced co-operation in global trade, and sovereign debt risks which together create the conditions for a global economic slowdown. Our objective is to explore CCP resilience to current risks facing the global financial system and identify potential vulnerabilities that could amplify risks to financial stability.

This scenario has been developed using a new methodology.^{footnote [2]} Previously, we had scaled up specific historical episodes to target a level of severity^{footnote [3]} at each service. In contrast, this year we have sampled scenarios from a multivariate distribution fitted to historical market shocks. This new approach, which is outlined in more detail in the linked publication, supports our objective of ensuring the resultant scenario is extreme but plausible, delivers consistency across Clearing Services, and captures the key risks we are seeking to assess.

The resulting scenario, chosen to align with the narrative above, is equivalent to a 1 in 3,500 event when assessed relative to a historical distribution. The scenario includes sharp declines in equity markets, rising interest rate expectations and falls in price for many commodities markets. Table B shows the shocks applied to key risk factors at each service.

In total, we specified shocks to ~900 market prices and rates. Each CCP was required to extrapolate the individual risk factor shocks to all products and exposures within their respective clearing businesses. This extrapolation was undertaken in a manner consistent with the overall scenario narrative and intended severity of the Market Stress Scenario. The Bank reviewed each CCP’s approach to extrapolation.

Extensions of the Market Stress Scenario

The 2025 CCP Stress Test also includes three additional ‘multiplier’ scenarios as part of our sensitivity testing, which explores scenarios and assumptions that deliberately go well beyond historical experience and regulatory requirements. These are constructed by applying linear multipliers (of -1.0x, 1.5x and 2.0x respectively) to each of the individual risk factor shocks in the Market Stress Scenario.

Additional scenarios

Building on our analysis from last year, we have used our internal stress testing models to explore CCP resilience against a much wider set of hypothetical scenarios, to identify potential vulnerabilities. Our updated methodology for generating scenarios allows us to generate a large number of scenarios – in this case 50,000 – to broaden our analysis of CCP resilience.^{footnote [4]} From this initial set of scenarios, we filter scenarios based on severity and similarity to obtain a set of hypothetical scenarios at service level that:

1. are grounded in historical relationships and include breaks in the correlations between key products;
2. are extreme but plausible for at least one service; and
3. cover a very large combination of shocks to risk factors.

By applying the same set of scenarios to data on cleared positions submitted by CCPs, we are able to use our internal stress-test models to provide estimates of the shocks, or combinations of shocks, which could exhaust pre-funded resources at CCPs. The methodology and results are discussed more fully in Box A.

Reference date

The Market Stress Scenario and additional alternative scenarios are applied based on the 26 March 2025 reference date. This date was selected to be generally representative of CCP margin and notional exposures, across all services, of the period since the conclusion of the Bank’s previous exercise.^{footnote [5]} The reference date was deliberately chosen to precede the onset of tariff-related market volatility in April, as the scenario incorporated similar dynamics. This ensured that the shocks were not already partially embedded in CCPs’ models.

The reference date determines the market prices and rates to which the risk factor shocks are applied, as well as CCP exposures and resources. Clearing Member defaults are assumed to occur after the end of day on the reference date, but before markets open the following working day. At this point, the Bank assumes that: (i) no payments are exchanged between CCPs and defaulting Clearing Members; (ii) no position changes are accepted; and (iii) no further payments or margin contributions are made to CCPs by any Clearing Member.

5: Credit Stress Test

The Credit Stress Test assesses whether each UK CCP has sufficient resources within the default waterfall to withstand a stress event combining severe market shocks and default of its members. This section starts by detailing the results of the core credit only stress test, which focuses on a Cover-2 default. Next, we extend the analysis to account for additional costs associated with liquidating the Cover-2 defaulters’ concentrated positions (the ‘Credit and Concentration Stress Test’). We then consider the impact of different groups of defaulters to test the efficacy of the Cover-2 standard (‘Cover-X analysis’). Finally, using data from previous CCP Stress Tests, we explore potential drivers of change between the years.

In all instances, the financial impact is measured relative to the resources held in the CCP’s default waterfall. The first layer of this waterfall is the resources provided by the defaulter themselves in the form of initial margin and default fund contributions. If these are not sufficient, then CCPs must use a portion of their own resources, known as ‘skin in the game’ (SITG). The last layer of pre-funded resources are contributions of non-defaulting clearing members to the mutualised default fund. CCPs can use their ‘Powers of Assessment’ to call additional, non-prefunded, resources from non-defaulting clearing members should the losses exhaust pre-funded resources.^{footnote [6]}

Core Credit Stress Test

Chart 1 shows the impact of a Cover-2 default. The lower section of the chart shows the losses in excess of the defaulting members’ own resources, which must be covered using the CCP’s own capital or the default fund contributions of non-defaulting Clearing Members. In the chart, these are labelled as the Stress Loss Over Member Resources (SLOMR) – for each Clearing Service. The top section of the chart shows the resulting consumption of resources within the default waterfall. The chart shows the results of the Credit Stress Test under the conservative assumption that no clients of the defaulting clearing members are able to ‘port’, or transfer, their portfolios to a non-defaulting clearing member, meaning the client portfolios must be liquidated alongside the clearing member’s own accounts.

The chart shows that under a Cover-2 default most Clearing Services would experience losses that go beyond the defaulters’ resources and require limited use of default fund contributions of non-defaulting members. However, all UK CCPs have sufficient default fund resources to absorb these losses. Below, we summarise the results for individual CCPs.

Chart 1: Standard Credit Stress Test results

Market Stress Scenario, CCP Clearing Service Cover-2 ^{(a) (b) (c) (d)}

Footnotes

• (a) Stressed losses over defaulting members’ resources (SLOMR) is the absolute amount (£ millions) by which losses exceed defaulters’ resources (initial margin and default fund contributions).
• (b) Percentage usage of dedicated CCP resources, known as ‘skin in the game’ (SITG).
• (c) Percentage usage of mutualised default fund (DF), consisting of non-defaulters’ default fund contributions.
• (d) Percentage usage of Powers of Assessment (PoA). PoA represents the total amount of non-prefunded resources that CCPs can call from non-defaulters.

For LCH, we see that the Cover-2 defaults at ForexClear and EquityClear do not generate losses beyond defaulter resources, with only small losses to non-defaulters’ resources at SwapClear and RepoClear. For RepoClear, the shocks applied to longer maturity Gilts – including an increase in the 10 year yield by 79 basis points, and the 30 year yield by 82 basis points – were approximately as severe as the historical worsts for those bonds, and so we take assurance from the fact that only a small proportion of the default fund (0.4%) was required in this scenario.

For ICEU’s F&O service, the scenario resulted in 19% of the default fund being used. The largest losses were driven by positions in Brent Oil contracts, to which the scenario applied a 17% price decrease over two days. These positions, combined with positions across oil products which received negative shocks, contributed to the overall impact on the default fund.

For LMEC, we see 12% of the default fund used in this scenario, driven by losses in longer dated copper contracts, to which the scenario applied a -10% shock. This year’s scenario explores the impact of negative price moves across a broad swathe of metals, consistent with what we would expect to see in a severe global economic slowdown.

Consistent with previous exercises, the assumption that clients of the defaulters cannot port to other clearing members has significant impact at ICEU and LMEC. For ICEU, which is most sensitive to this assumption, allowing all clients to port results in losses that can be contained within SITG, relative to the baseline assumption of no porting, which results in 19% of the default fund being used. One reason why this assumption has a larger impact at ICEU and LMEC than LCH is because client clearing constitutes a larger portion of activity, meaning there are more positions that are eligible to port.

The Bank considers porting to be an important part of the default management process, while recognising that there are challenges which decrease the overall likelihood of successful transfers of client portfolios after a Clearing Member default. As such, the Bank has taken steps to propose changes to the regulations to increase the probability of successful transfers, which can be found in chapters 15 and 16 of the Bank’s consultation on the repeal and replace of UK EMIR.^{footnote [7]}

Credit and Concentration Stress Test

The Credit and Concentration Stress Test extends the core analysis to account for the potential costs of liquidating concentrated positions held by defaulters. If the Cover-2 members together hold a position in certain products that is large relative to the depth of the market, then the CCP might incur additional costs when liquidating these positions.

While the impact of the core stress test can be calculated precisely using the data submitted by CCPs, the costs of liquidating concentrated positions are much harder to observe or calculate and so must be modelled. The Bank’s methodology assumes that concentration costs can be implied from the additional market risk that defaulters’ positions would be exposed to if, instead of being liquidated all at once and potentially moving the market, they were instead liquidated gradually, at a rate that is small relative to the overall market depth.

This year, we retain the original methodology that the Bank has developed for calculating these additional costs, which is based on the assumptions below.^{footnote [8]} Assumptions on liquidation rates and market depth are applied separately for each product within the portfolio and for products of different maturities.

1. Market depth: We assume that the depth of the market can be implied from the daily average traded volumes of that specific contract over the previous 12 months.
2. Liquidation rates: Our baseline assumption is that the CCP can only liquidate 25% of our estimate of market depth per day and this assumption aims to approximate the additional market risk borne by holding the position for a longer period.

For products and contracts which do not trade frequently, but have high levels of open interest, assumption (1) can be seen as conservative. Under this assumption, these contracts would appear to be deeply illiquid, and the CCP would not be able to liquidate a significant proportion of the position without materially impacting market prices. Assumption (2) also plays a significant role in estimating the overall liquidation costs for concentrated portfolios. The smaller the proportion of a position that a CCP can liquidate every day, the longer the liquidation process can take, which increases the costs that must be borne by the default waterfall.

Chart 2 shows the results of adding concentration costs under our baseline assumptions. The results show that concentration costs can significantly increase the total losses across the system, but all services held sufficient pre-funded resources to absorb the losses, even under conservative assumptions.

Including concentration costs does not affect all services equally. Similarly to previous years, we see the most significant impacts at ICEU and LMEC, where default fund usage increases from 19% to 39%, and 12% to 53% respectively. The impact at these services is sensitive to the specific assumptions used to estimate market depth, especially in products that might be traded infrequently, but have deep open interest.^{footnote [9]}

For LCH, the results show no additional impact at RepoClear, reflecting the large size of the Gilt market. However, ForexClear would require 16% of the default fund to be used when the costs of liquidating concentrated positions are added, driven by positions in US dollar and Brazilian real contracts. Without these additional costs the losses could be contained within the defaulter’s resources.

Chart 2: Credit and Concentration Stress Test results

Market Stress Scenario, CCP Clearing Service Cover-2, no porting ^{(a) (b) (c) (d)}

Footnotes

• (a) Stressed losses over defaulting members’ resources (SLOMR) is the absolute amount (£ millions) by which losses exceed defaulters’ resources (initial margin and default fund contributions).
• (b) Percentage usage of dedicated CCP resources (SITG).
• (c) Percentage usage of mutualised default fund (DF), consisting of non-defaulters’ default fund contributions.
• (d) Percentage usage of Powers of Assessment (PoA). PoA represents the total amount of non-prefunded resources that CCPs can call from non-defaulters.

Cover-X analysis

The Cover-X analysis extends the Credit Stress Test to explore whether CCP pre-funded resources are also sufficient to absorb losses of alternative combinations of defaulters. By testing CCP resilience against different groups and numbers of defaulters, we can assess the coverage provided by the Cover-2 Standard, which mandates that CCPs hold sufficient pre-funded resources to absorb losses under a Cover-2 default. The groups we include are:

• System-wide Cover-2 default: the default of the pair of Clearing Member groups which, if defaulted at all three CCPs, generate the largest impact on mutualised resources across all CCP Clearing Services in aggregate under the baseline Market Stress Scenario. This captures interconnectedness across the financial system, given the overlapping memberships of UK CCPs.
• Non-bank financial institutions (NBFIs): default of all Clearing Member groups defined as non-bank entities, such as commodities brokers or pension funds.
• Non-financials: default of all Clearing Members groups defined as non-financial entities, such as industrial or manufacturing entities active in commodities markets.
• Members with an elevated probability of default: default of all Clearing Member groups with a one-year estimated probability of default greater than 0.2%, as defined by Bloomberg.^{footnote [10]}

Across these defaulter groups, we calculate the impact inclusive of concentration costs, to account for the risk of a large number of similar entities taking similar positions.

The results are shown in Chart 3. The results show that across all combinations analysed, there are no scenarios which result in higher losses than a Cover-2 default and therefore losses are within the CCPs’ pre-funded resources. This year, the baseline Market Stress Scenario included negative shocks to commodity and metal markets, primarily impacting positions held by larger global banks, meaning the impact of defaulting NBFIs or non-financial clearing members is less severe. This is shown by the fact that only a small proportion of NBFI clearing members experience losses beyond their own resources upon default.

For LMEC, for example, none of the 18 NBFI members experience losses above their own resources, whereas in our 2024 stress test nine of these members experienced such losses. This reflects the fact that in our 2024 stress scenario the directions of shocks of commodity and metals markets were reversed. For ICEU, the trend is similar, only three of the 18 NBFIs defaulted in this exercise experience losses above their own resources, compared to eight in 2024. For LCH, in both years, 13 NBFI members were defaulted, with none experiencing losses above their own resources.

From these results, we note that under the Market Stress Scenario, CCPs have sufficient pre-funded resources to absorb losses in a wide range of different default scenarios, including those that include the potential simultaneous defaults of more than two members. This provides confidence that the Cover-2 standard delivers a meaningful quantum of resources that can withstand a broad range of scenarios.

Chart 3: Cover-X Stress Test results

Market Stress Scenario, Cover-X combinations, No porting ^{(a) (b) (c) (d)}

Footnotes

• (a) Stressed losses over defaulting members’ resources (SLOMR) is the absolute amount (£ millions) by which losses exceed defaulters’ resources (initial margin and default fund contributions).
• (b) Percentage usage of dedicated CCP resources (SITG).
• (c) Percentage usage of mutualised default fund (DF), consisting of non-defaulters’ default fund contributions.
• (d) Percentage usage of Powers of Assessment (PoA). PoA represents the total amount of non-prefunded resources that CCPs can call from non-defaulters.

Comparing stress test results over time

With the benefit of additional years of data, we can investigate the potential drivers of change in the results of the CCP Stress Tests over time.

Overall, UK CCPs experienced lower levels of resource consumption in the 2025 stress test relative to the 2024 exercise. ICEU and LMEC experienced higher resource consumption in 2025 than 2023, with the impact on LCH being slightly more mixed, with SwapClear and RepoClear experiencing higher losses in 2025, while ForexClear and EquityClear did not need to use non-defaulter resources in either year. On its own, this is not sufficient to make direct comparisons of CCP resilience between years. This is because the results of the stress test reflect various factors, including the way in which the different scenarios interact with the exposures held at the CCP on the reference date and the resources held at the CCPs at the time of the exercise.

Chart 4 shows the aggregated levels of initial margin and default fund resources, using data submitted by CCPs on different stress test reference dates. We see that the quantum of initial margin held increased in 2023 as CCP models reacted to the various stress events of 2022. Margin levels returned to lower levels in 2024, which partially explains the difference in impact on mutualised resources, especially as default fund levels fell between 2022 and 2024. This does not explain all the difference between the 2023 and 2024 results, as the calibration of the 2024 Market Stress Scenario included large shocks to key products with large and concentrated positions. From 2024 to 2025 we note a simultaneous, albeit small, increase in both initial margin levels and default fund levels, driven by increases in volumes in some services.

Chart 4: Aggregate initial margin levels across UK CCPs ^(a)

Footnotes

• (a) The left axis relates to the total initial margin held at UK CCPs, in £ billions, and the right axis relates to the aggregate default fund resources held at UK CCPs, in £ billions. This data is sourced from the Bank’s regular supervisory data collection.

We use an internal stress-testing model to estimate the impact of changes in resources, positions and the scenario across successive stress tests. To do this, we estimate the impact of each Market Stress Scenario on members’ positions on each reference date, using data submitted by the CCPs. This allows us to estimate the impact three distinct scenarios would have on a common set of positions – effectively isolating the impact of changing the scenario. Conversely, by applying the same scenario to different data on CCPs’ members’ positions and available resources, we can isolate how changes in resources and exposures affect the results. This exercise is based on linear modelling of the impact of different risk factor movements on profit and loss impact within services rather than the full revaluations of positions undertaken by CCPs, meaning they will not be as precise as the core results above.

Chart 5 shows the results. The individual lines show the impact of each Market Stress Scenario on mutualised losses, based on submissions of exposures and resources provided by the CCP on each reference date. The different levels of the lines highlight the different impact of each scenario. The different points on each line show the impact of the resources and exposures in each exercise.

The chart shows that across all three years’ exposures, the 2024 Market Stress Scenario had the highest impact in terms of losses over defaulter resources. This is expected given the nature of that year’s scenario, which included shocks to some key products which went beyond historical worsts.^{footnote [11]} The chart also shows that the 2023 and 2025 Market Stress Scenarios had a similar direct impact on CCPs. However, the higher resource levels held at CCPs in 2023 resulted in lower mutualised losses. We estimate that the losses generated by all Market Stress Scenarios would have been absorbed within pre-funded resources in all services across all three years.

The dynamics we have seen in recent years are consistent with how we would expect CCPs’ financial models to respond to market conditions, which have a direct impact on resource requirements at CCPs. And so we do not interpret the increased use of default fund resources from 2023 to 2025 as indicative of a change in resilience. We attribute the drop in resources consumed compared to the 2024 CCP Stress Test to be driven by the choice of scenario.

Chart 5: Aggregate impact of Market Stress Scenarios in different years ^(a)

Footnotes

• (a) Each line represents the aggregate SLOMR for all three UK CCPs when the relevant year’s baseline Market Stress Scenario is applied to the data submitted in each of the three years. The impact is estimated by applying the Bank internal linear desk-based model to the relevant CCP’s data submissions in each year.

6: Extensions of the Credit Stress Test

Alongside the core Credit Stress Test we use additional sensitivity analysis and reverse stress testing to better understand the resilience of CCPs to combinations of increasingly severe assumptions. Changing these assumptions creates scenarios beyond historical precedents and regulatory requirements.

The Opposite Direction Scenario analysis subjects CCPs to a scenario in which the directions of all shocks (except volatility shocks) in the Market Stress Scenario are reversed. This analysis can identify whether CCPs are able to absorb shocks very different in nature from the baseline scenario and recent market experience, providing us with additional insights.

The ‘Reverse Stress Test’ assesses CCPs against increasingly severe combinations of assumptions on scenario severity, the number of defaulters and the different calculations of concentration costs. While this is not strictly a reverse stress test, as we do not identify precise ‘breaking points’ at each CCP, the combinations of more severe assumptions enable us to identify points of vulnerability at each CCP.

Opposite Direction Scenario

Reversing the direction of the baseline Market Stress Scenario allows us to explore whether the CCPs are particularly exposed to market moves in a specific direction. However, as this scenario is simply the inversion of the baseline, it has not been calibrated to a specific level of plausibility and consistency in severity across all CCPs.

Chart 6 shows the results of this exercise and shows that all services (except for EquityClear) experience higher levels of losses than under the baseline scenario.

Chart 6: Credit Stress Test, Opposite Direction Scenario

-1.0x Market Stress Scenario, CCP Clearing Service Cover-2, No porting ^{(a) (b) (c) (d)}

Footnotes

• (a) Stressed losses over defaulting members’ resources (SLOMR) is the absolute amount (£ millions) by which losses exceed defaulters’ resources (initial margin and default fund contributions).
• (b) Percentage usage of dedicated CCP resources (SITG).
• (c) Percentage usage of mutualised default fund (DF), consisting of non-defaulters’ default fund contributions.
• (d) Percentage usage of Powers of Assessment (PoA). PoA represents the total amount of non-prefunded resources that CCPs can call from non-defaulters.

For ICEU, this can be explained by the fact that when the negative shocks to oil products – including Brent and WTI – are reversed, they move beyond maximum price increases historically observed in those products and so represent a more extreme stress.

For LMEC, we note that although losses over defaulter resources increase under this scenario, a smaller proportion of the default fund is depleted. Whereas under the baseline Market Stress Scenario, the Cover-2 defaulters were large international banks, under the Opposite Direction Scenario the defaulters are NBFIs, which have smaller default fund contributions relative to the larger clearing banks, meaning there is a larger proportion of the default fund remaining after the defaulter’s resources are removed.

For LCH, we observe that all services, except for EquityClear, experience higher levels of SLOMR under the Opposite Direction Scenario. This is most pronounced in SwapClear, in which the SLOMR increases by more than 2x under this set of shocks.

Reverse Stress Test

The Reverse Credit Stress Test systematically subjects CCPs to increasingly severe assumptions on scenario severity, the number of defaulters and the calculation of concentration costs. Each of these assumptions is adjusted to levels of severity that intentionally go well beyond historical precedents and regulatory requirements and in combination are very extreme.

The aim of this analysis is to identify the combinations of assumptions that might fully deplete both pre-funded and non-prefunded resources at each Clearing Service. We do this by asking CCPs to submit data on the impact of specific ‘multiplier’ scenarios.

The Credit Reverse Stress Test uses the same calculation methodology as the Credit Stress Test (Annex A), with adjustments to the following input assumptions:

• Scenario severity: We apply scenarios that are, respectively, -1x, 1.5x and 2x of our Market Stress Scenario with the aim of identifying shocks that exhaust the pre-funded resources in a service.
• Number of defaulters: By increasing the number of defaulters from one to five, this analysis seeks to understand the marginal impact on losses that each additional defaulter, chosen in order of exposures, adds.
• Liquidation rates: we increase the severity of assumptions used to model concentration costs. Specifically, the volume of defaulting Clearing Members’ positions that we assume can be liquidated each day before giving rise to concentration premiums is reduced from 25% down to 5% of market depth.

Chart 7 presents aggregate stressed losses over member resources across all CCP Clearing Services as the severity of each assumption is adjusted individually. In isolation, increasing the severity of the scenario has the greatest impact on stressed losses over member resources, compared to increasing the number of defaulters or increasing the severity of the Bank’s concentration cost assumptions.

Chart 7: Credit Reverse Stress Test results

Aggregate SLOMR across all CCP Clearing Services ^{(a) (b) (c)}

Footnotes

• (a) Each line illustrates the impact of increasing the severity of one assumption while holding all other assumptions constant. Where the number of defaulting Clearing Member groups is held constant, the identity of the Clearing Member groups can change according to the dynamic Cover-2 methodology.
• (b) Stressed losses over members’ resources (SLOMR) is the absolute amount (£ billions) by which losses exceed defaulters’ resources (initial margin and default fund contributions).
• (c) ‘25%’, ‘15%’, ‘10%’, and ‘5%’ represent the percentage of daily average volume traded for each product assumed can be liquidated daily without a price impact. A lower liquidation rate implies a reduction in the market’s ability to absorb CCP positions before giving rise to concentration costs. N/A represents exclusion of concentration costs.

Chart 8 presents the results when combining changes in all three input assumptions simultaneously. The chart illustrates which layers of each CCP Clearing Service’s default waterfall experience depletion under each combination of assumptions. The different shades in each cell indicates the proportion of each layer depleted – with darker shades indicating larger losses. As expected, as we apply more extreme and conservative assumptions – that go well beyond regulatory requirements – we start to see losses that exceed CCPs’ default funds. But across assumptions all CCPs other than RepoClear experience less depletion of their resources than in the 2024 stress test.

Chart 8: Credit Reverse Stress Test results

CCP Clearing Service Cover-N, No porting ^{(a) (b) (c) (d) (e) (f)}

Footnotes

• (a) Percentage usage of dedicated CCP resources (SITG).
• (b) Percentage usage of mutualised default fund (DF), consisting of non-defaulters’ default fund contributions.
• (c) Percentage usage of Powers of Assessment (PoA). PoA represents the total amount of non-prefunded resources that CCPs can call from non-defaulters. PoA are assumed to be equal to the minimum of non-defaulting Clearing Member groups’ default fund contributions multiplied by three, or the non-defaulting Clearing Member groups’ default fund contributions multiplied by the number of individual defaulting Clearing Members.
• (d) Losses beyond PoA, presented with reference to the size of PoA. For example, 100% PoA equivalent where losses beyond PoA are of the same magnitude as PoA.
• (e) ‘25’, ‘15’, and ‘10’ represent the percentage of daily average volume traded for each product assumed can be liquidated daily without a price impact. A lower liquidation rate implies a reduction in the market’s ability to absorb CCP positions before giving rise to concentration costs. N/A represents exclusion of concentration costs.
• (f) Numbers on the y-axis represent the number of Clearing Member groups assumed to default.

For ICEU, generating losses which exceed the default fund requires increasing the scenario severity to 1.5x of the baseline Market Stress Scenario, which includes market moves well beyond historical worsts. It would require more than two defaults or more severe assumptions on concentration costs for Powers of Assessment to be exhausted, even under a scenario twice as severe as the baseline. Under the baseline scenario, it requires at least three defaulters and additional concentration costs to exhaust the default fund.

At LMEC, more extreme combinations of assumptions are required to exhaust resources when compared to 2024. In the absence of concentration costs, LMEC is resilient to a market stress and Cover-2 default of 1.5x the Market Stress Scenario. And it would take the default of more than two members to exhaust LME’s Powers of Assessment, even in a scenario twice as severe as the baseline. As discussed above, including concentration costs has a greater impact at LME.

Consistent with the results of the Credit Stress Test, it generally requires more severe assumptions to exhaust pre-funded resources within LCH services. Notably, there are no combination of assumptions that lead to mutualised resources being used at EquityClear. For RepoClear, the service is resilient to a Cover-2 default with a scenario twice the baseline. For SwapClear, it requires more than two defaulters and the inclusion of concentration costs to exhaust the default fund under the 1.5x scenario and we do not identify any scenarios that exhaust Powers of Assessment.

Overall, CCPs are more resilient to increasingly severe combinations of assumptions than in the 2024 exercise. This is in line with the results above and partly reflects the shape of the scenario and the fact that fewer shocks went beyond historical worsts. In this context, we take additional assurance from the fact that CCPs can withstand more severe combinations of assumptions without depleting their resources.

7: Liquidity impacts

The Bank’s stress test also considers the impact on liquidity, both from the perspective of CCPs and from the perspective of their members and clients.

For CCPs, there is a risk that a severe market stress combined with the default or failure of two of their members could result in a liquidity shortfall, meaning CCPs do not have the available liquid resources to meet their liquidity needs. This risk was explored in the 2023 stress test, in which we concluded that CCPs were resilient and liquidity risks were generally structural in nature rather than the impact of a specific market stress. This year, we have probed these risks qualitatively to identify how these risks have changed.

For CCPs’ members and clients, there is a risk that liquidity demands from CCPs in a stress via initial and variation margin calls could put pressure on their own liquidity. An increase in liquidity demand can put pressure on the wider system if it results in forced selling of assets (a dynamic explored in the Bank’s 2024 System Wide Exploratory Scenario).^{footnote [14]} In this year’s test we assess the impact of initial and variation margin calls, in order to support the Bank’s wider surveillance and risk assessment.

Liquidity risks to CCPs

The 2025 CCP Stress Test does not include a full liquidity stress test, rather we used a qualitative questionnaire to explore how potential risks to CCP liquidity exercise may have evolved since the 2023 exercise.

The 2023 Liquidity Stress Test found that all CCPs maintained a positive liquidity balance under stress, across all major currencies, even under very conservative assumptions about disruption to CCPs’ ability to mobilise liquid resources. Sensitivity testing explored the impact of wider disruption and identified that LMEC and ICEU were potentially more exposed to the failure of an investment agent whereas LCH was relatively more exposed if unable to liquidate non-cash collateral. These results generally reflect more structural factors and strategic considerations of CCPs – rather than the impact of a specific market stress – and so we probe whether CCPs’ approaches have changed and whether we would expect to see substantive changes to the results.

The questionnaire covered: CCPs’ assessment of liquidity risks and how these have changed since the 2023 stress test; emerging risks identified by CCPs and their approach to managing these risks; and the available actions which CCPs could take to alleviate any shortfalls.

Liquid resources have fallen compared to 2023, reflecting the drop in overall margin levels, but CCPs continue to have sufficient liquid resources to manage the default or failure of two members, including service providers. The Bank has corroborated this assessment using its supervisory data collection. We also note that CCPs have taken steps to reduce concentration risks among service providers, by expanding their set of repo counterparties or distributing investment allocations more evenly between service providers.

CCPs highlighted geopolitics as a potential area of emerging liquidity risks, but noted that these risks were not currently affecting their ability to access markets that are key for UK CCPs – including USD, EUR and Sterling markets. CCPs also noted that they were taking steps to adapt their risk management to market trends, including the introduction of a mandate for US Treasury repo clearing.

Lastly, the questionnaire asked CCPs about the steps that would be taken in the event of a liquidity shortfall and assessed the implications for financial stability. In the event of any potential liquidity shortfall, CCPs have a variety of options and detailed plans and preferences for how to manage such an event. Standard market operations (for example, raising cash on repo or FX markets) were prioritised. Other options available to the CCPs, which include measures that materially impact members’ liquidity – such as haircutting or delaying payments of variation margin to members – were considered last resorts.

Liquidity risks to clients and members

In a stress, liquidity conditions can rapidly deteriorate and members and clients – in particular NBFIs – may face additional liquidity demands. These dynamics and the consequences for the wider financial system were explored by the Bank in the 2024 system-wide exploratory scenario (SWES), which included analysis of the liquidity demands originating from CCPs via margin calls.

CCPs provided information on the value of initial and variation margin calls under the Market Stress Scenario for each house and client account. CCPs use bespoke models to calculate initial margin requirements, which tend to increase following unprecedented changes in market prices and volatility. As such, CCPs provided the Bank with modelled estimates of the change in initial margin requirements that would result from the Market Stress Scenario.

Chart 9 shows gross flows of variation margin between UK CCPs and other parts of the financial system. The figures above the axis show variation margin calls to be paid to the CCP by members and clients; figures below the axis show margin paid out by the CCP. Where possible, margin calls are allocated to the relevant sector, for example, banks, non-banks and other (generally government or international organisations). However, this classification is not possible for omnibus client accounts, which may include both NBFIs and smaller banks.

The Market Stress Scenario generates gross variation margin demands of about £90 billion, the majority of which fall on banks. On aggregate, banks are estimated to face a small net demand of about £2.5 billion. NBFIs are estimated to face gross calls for variation margin payments to CCPs of £17 billion, rising to up to £40 billion if unclassified accounts are included.

Chart 9: Gross variation margin calls by CCP and by sector

Baseline Market Stress Scenario, aggregate currency level (GBP equivalent) ^(a)

Footnotes

• (a) Positive quantities are those paid to a CCP, negative quantities are paid out to Clearing Members. The ‘Other’ category consists of non-financial and state-like entities, while the ‘unclassified accounts’ are those with missing data or entities from different sectors – generally these are client accounts.

Chart 10 shows gross initial margin flows. As above, payments made by members and clients to CCPs are shown above the axis, payments to members and clients are shown below. Gross initial margin calls are about an order of magnitude smaller than variation margin calls – £8.4 billion – but do represent a net liquidity demand on the wider system of around £7 billion. Almost half of initial margin demands fall on banks, with £1.2 billion falling on NFBIs.

Chart 10: Gross initial margin calls by CCP and by sector

Baseline Market Stress Scenario, aggregate currency level (GBP equivalent) ^(a)

Footnotes

• (a) Positive quantities are those paid to a CCP, negative quantities are paid out to Clearing Members. The ‘Other’ category consists of non-financial and state-like entities, while the ‘unclassified accounts’ are those with missing data or entities from different sectors – generally these are client accounts.

When we look at the largest aggregate margin demands, these tend to fall on major global banks and represent a very small fraction of their overall holdings in collateral classed as high-quality liquid assets (HQLA), meaning that they are likely to be able to meet these demands. The liquidity demands facing NBFIs are significantly smaller than those estimated in the SWES, suggesting that they would not present a risk to the wider system. However, NBFIs may still need to liquidate or repo assets to meet these demands. The Bank has supported work by international standard setting bodies to improve the transparency of margin calls and the preparedness of financial institutions and final proposals have recently been published.^{footnote [15]}

8: Conclusions and next steps

Overall, the results of the 2025 CCP Stress Test show that UK CCPs have sufficient pre-funded resources to absorb the losses generated after a Cover-2 default under this extreme but plausible Market Stress Scenario. CCPs continue to have sufficient resources under this scenario when considering the additional costs of liquidating concentrated positions.

CCPs experienced less depletion of pre-funded resources in the 2025 exercise relative to the 2024 stress test. Our internal stress-test models indicate that this reflects the shape and direct impact of the scenario, which included fewer shocks beyond historical worsts than the 2024 scenario. But we also note greater depletion of mutualised resources than in the 2023 stress test. This is consistent with CCPs partially unwinding pre-funded resources that had increased following the market volatility in 2022.

Consistent with the exploratory aims of the CCP Stress Test, the exercise also includes sensitivity testing and reverse stress testing that goes beyond regulatory requirements. These aim to identify potential pockets of vulnerability that may exist outside the Cover-2 population or under shocks that go beyond ‘extreme but plausible’.

• The Cover-X analysis goes beyond a Cover-2 default, in order to uncover potential vulnerabilities that may not be captured when focussing on the Cover-2 population – including non-bank and non-financial clearing members. None of these extensions generated loss amounts greater the Cover-2, giving us confidence in this standard as a basis for sizing CCPs’ resources.
• The Opposite Direction Scenario reverses the direction of the Market Stress Scenario in order to survey a wider range of shocks. In practice, the reversed shocks tend to sit further into the tail, or beyond, the historical distribution. Although all services other than EquityClear see greater SLOMR under this scenario, these losses remain contained within default funds.
• In the Credit Reverse Stress Test, CCPs are tested against different combinations of Market Stress Scenarios and assumptions on the number of defaulters that go beyond historical precedents, as well as the inclusion of more conservative estimates of concentration costs. Overall, CCPs deplete less of their resources under increasingly severe assumptions than in 2024 and it takes a combination of very extreme assumptions for any CCP to exhaust their powers of assessment.

As an extension to this year’s stress test, we use our internal models to estimate the impact of a wider range of scenarios on CCPs’ resources. The scenarios are drawn from a distribution fitted to historical data, and include scenarios that stretch correlations between different products and go beyond historical precedents. We filter from an initial set of 50,000 scenarios to approximately 1,000 scenarios based on severity and similarity. We then estimate the losses and impact on CCPs’ resources using an internal model. While not as precise as the core Credit Stress Test, which is based on full scenario revaluations undertaken by CCPs, this process enables us to survey a wider range of potential risks. We find only a small number of scenarios in the tail of the distribution that could present a risk to the resources of non-defaulting members. This wider assessment, in conjunction with the core stress test, allows us to more comprehensively test CCPs’ overall resilience. Going forward, we plan to make greater use of this approach to assess CCP resilience on an ongoing basis and respond to emerging risks.

The Bank will use the findings from the 2025 CCP Stress Test to support and inform its ongoing supervision and regulation of UK CCPs. We plan to follow up with the three CCPs in scope to share and discuss the results and pockets of risk identified. We will also share relevant results with other regulators and authorities.

Looking ahead, we will not be conducting a full public stress test of UK CCPs in 2026. We plan to build on work done this year and continue to develop our internal stress testing tools to support our objective of conducting more dynamic and efficient testing of a wider range of risks and scenarios. The next public exercise will take place in 2027.

Annexes

• Annex A: Credit Stress Test methodology

  Methodology

  The Credit Stress Test methodology aims to reflect the processes and mechanics of a Clearing Member default scenario, based as closely as possible on the applicable regulations and CCPs’ rulebooks.

  The Bank collects data from CCPs on financial resources held (including margin requirements and margin collateral, default fund contributions, and CCPs’ own capital),^{footnote [16]} Clearing Member and client positions, and on the impact of each of the Market Stress Scenarios on Clearing Members’ and clients’ profit and losses. The Bank relies on CCPs’ models to revalue collateral and positions given the complexity of some of the products cleared by UK CCPs. The Bank validates the data submitted by CCPs against other information sources available.

  Using this input data, the Bank assesses the impact on individual CCP Clearing Services’ financial resources under the applicable Market Stress Scenario and default assumptions, following the steps below. Where additional modelling assumptions are required – for example in the estimation of concentration costs – the Bank applies its own bespoke and conservative models.

  Step 1 – Calculation of surplus or deficit of resources at the individual account level

  The Bank first calculates the surplus or deficit of resources for each individual Clearing Member house account and client account. This is determined by comparing the PnL impact of the relevant Market Stress Scenario, estimated concentration costs where applicable, and the applicable account-level pre-funded resources. These calculations are based on margin requirements, rather than total margin collateral, to reflect the possibility that Clearing Members may withdraw excess collateral from CCPs in the run-up to a default event.

  Step 2 – Calculation of surplus or deficit of resources at the Clearing Member level

  Next, the overall impact for each individual Clearing Member is determined based on the surplus or deficit of resources at each of its accounts, and the relevant account segregation rules. Surpluses and deficits on house accounts are generally aggregated, as CCP rules allow any surplus on Clearing Members’ house accounts to be used to offset any deficits on their client accounts. Balances at client accounts are only aggregated where: (i) those accounts have a deficit; and (ii) those accounts are not assumed to be ported (ie transferred) to other (non-defaulting) Clearing Members. This reflects CCP rules which stipulate that any surplus on clients’ accounts must be returned to those respective clients and cannot be used to offset deficits elsewhere.

  The Bank considers alternative assumptions regarding CCPs’ ability to successfully port client accounts (detailed in Table 1.A) to assess the impact of successful porting on CCPs’ resilience. Where porting of client accounts is assumed, ported accounts would be moved across to a new Clearing Member with all their positions and resources and so are excluded from the rest of the calculation process.

  Table 1.A: Credit Stress Test alternative porting assumptions

  Porting assumption	Description
  No porting	No client accounts port from defaulting Clearing Members to non-defaulting Clearing Members. This is the most conservative porting assumption in the Credit Stress Test.
  Segregated client accounts port	Client accounts that are individually segregated (ISEG) or legally segregated operationally comingled (LSOC) are assumed to successfully port from defaulting Clearing Members to non-defaulting Clearing Members. Omnibus accounts do not port from defaulting Clearing Members to non-defaulting Clearing Members.
  All client accounts port	All client accounts are assumed to successfully port from defaulting Clearing Members, including ISEG, LSOC, and omnibus accounts.

  Step 3 – Calculation of surplus or deficit of resources at the Clearing Member group level

  Clearing Members are then grouped together into Clearing Member groups when they are under the same corporate/legal structure and/or have particularly close economic relationships. This reflects the likelihood that all Clearing Members within a Clearing Member group would default together when a default occurs.

  The surplus or deficit of resources for each Clearing Member group is then calculated based on the net surplus/deficit of each individual Clearing Member within that Clearing Member group. Under CCPs’ rules, defaulting Clearing Members are resolved separately, even if they are part of the same corporate group. For Clearing Members with a surplus, this surplus therefore cannot be used to offset losses elsewhere in the Clearing Member group. For Clearing Members with a deficit over their margin resources, this deficit is compared against their own default fund resources and then aggregated to calculate stressed losses over defaulting members’ resources at the Clearing Member group level.^{footnote [17]}

  Step 4 – Default of selected Clearing Member groups

  The Credit Stress Test methodology can test any combination of defaulting Clearing Member groups. The initial focus is on the default of the Cover-2 population, which is determined algorithmically for each CCP Clearing Service by calculating losses for every potential pair of defaulting Clearing Member groups.^{footnote [18]}

  This is complemented by the Cover-X analysis, which considers the default of customised populations of Clearing Member groups. This includes an analysis of the system-wide Cover-2 population, defined as the two Clearing Member groups whose default leads to the greatest aggregate stressed losses over defaulting members’ resources across all CCP Clearing Services. It also includes populations of Clearing Member groups based on common characteristics, such as entity type or industry, and based on Clearing Members’ probability of default.

  Step 5 – Calculation of depletion of financial resources held under CCPs’ default waterfalls

  After selecting the defaulting Clearing Member groups, the resulting stressed losses over defaulting members’ resources are compared to the other resources available to each CCP Clearing Service under their default waterfalls. These resources are drawn upon in the following order: SITG, the mutualised default fund and Power of Assessment.

   

• Annex B: Glossary

  Baseline Market Stress Scenario – A hypothetical Market Stress Scenario designed by the Bank of England. This scenario includes escalating concerns about global fragmentation, represented by reduced co-operation in global trade, and sovereign debt risks which together create the conditions for a global economic slowdown.

  CCP (central counterparties) – Financial Market Infrastructures sitting between the buyer and seller of a trade, guaranteeing the obligations under the contract agreed between the two counterparties. If one counterparty fails, the other is protected via the default management procedures and resources of the CCP.

  CCP Clearing Service – A distinct part of a CCP offering clearing for certain financial markets and types of products. Typically, each CCP Clearing Service maps directly to a single default fund.

  CCP skin in the game – A tranche of the CCP’s own capital that is utilised directly after the defaulter’s resources have been used to cover losses, but before any resources from non-defaulted members can be utilised.

  Clearing Member – A direct member of the CCP that submits trades either on their own behalf or on behalf of clients. The Clearing Member is financially responsible for the trade’s obligations, such as posting initial margin and variation margin, including on behalf of its clients.

  Clearing Member group – A group of entities, at least one of which is a Clearing Member, that form part of a legal entity or are closely economically integrated.

  Client – Counterparties that clear trades indirectly via a Clearing Member. These entities do not make contributions to CCPs’ default funds.

  Concentration costs – Additional costs that CCPs may face when they liquidate (through hedging or auction) large or concentrated positions of defaulters.

  Cover-2 – The two Clearing Member groups whose default generates the largest impact on resources/worst liquidity balance at each CCP Clearing Service/CCP under the relevant Market Stress Scenario.

  Cover-X – An alternative (ie not Cover-2) defaulter population at each CCP Clearing Service.

  Default fund – CCPs’ pre-funded mutualised resources contributed by Clearing Members. These resources are called upon after the defaulters’ own resources and the CCP’s own capital have been depleted.

  Defaulters’ own resources – The pre-funded resources, consisting of initial margin and default fund contributions, which a defaulting Clearing Member has posted to the CCP as collateral. These form the first layer of each CCP’s default waterfall.

  Default waterfall – The resources that a CCP can access to satisfy defaulting Clearing Members’ obligations, drawn in the following order: (i) defaulting Clearing Members’ pre-funded resources (initial margin and default fund contributions); (ii) CCP skin in the game (CCPs’ own capital set aside to absorb default losses); (iii) mutualised default fund contributions (pre-funded contributions of non-defaulting Clearing Members); and (iv) Powers of Assessment (non-prefunded resources CCPs can call from non-defaulting Clearing Members).

  Initial margin – Resources posted by a Clearing Member to cover the potential losses that could arise from that Clearing Member’s positions in the event of a default. A CCP will call upon the defaulting Clearing Member’s initial margin contributions before other resources within the default waterfall sequence to meet the obligations of a defaulting Clearing Member.

  Losses beyond Powers of Assessment – Outstanding losses after all previous layers of the default waterfall have been depleted, including Powers of Assessment. CCPs may use tools such as cash calls, variation margin gains haircutting and contract tear-ups where they experience losses beyond Powers of Assessment.

  Mutualised default fund contributions – Clearing Members’ contributions to a CCP’s default fund which can be used to absorb default losses beyond defaulters’ own resources and CCPs’ SITG. Utilised contributions require replenishing by non-defaulting Clearing Members.

  Non-bank Clearing Member group – Group that is not classified as a bank entity or another CCP.

  Non-financial Clearing Member group – Group that does not conduct banking activities or other financial activities.

  Non-prefunded resources – Additional financial resources that CCPs have the power to call from non-defaulting Clearing Members via Powers of Assessment.

  Omnibus client account – An account maintained by a Clearing Member at a CCP that contains more than one customer of the Clearing Member.

  Opposite Direction Scenario – A Market Stress Scenario in which the directions of all shocks (except volatility shocks) are reversed relative to the baseline Market Stress Scenario.

  Porting – Refers to the ability of CCPs to successfully transfer client accounts at defaulting Clearing Members to non-defaulting Clearing Members.

  Powers of Assessment – The non-prefunded resources a CCP can request from its Clearing Members in the event of a Clearing Member default. This can occur after the depletion of the Defaulter’s pre-funded resources, the CCP’s skin in the game and the default fund.

  Pre-funded resources – The total of all collateral held by CCPs that is available at the time of a potential default. This includes initial margin and default fund contributions of any defaulted Clearing Members, and default fund contributions of non-defaulting Clearing Members.

  Probability of default – The modelled probability that a chosen entity will default on its obligations over a specified period.

  PnL (profit-and-loss) – The observed increase/decrease in the value of a portfolio when this is priced at current market prices.

  Reference date – The start date for the CCP stress test. The reference date determines the market prices to which shocks are applied, as well as CCP exposures and resources.

  Risk factors – The individual market prices and rates to which shocks are applied in the Bank’s Market Stress Scenarios.

  Segregated client accounts (ISEG, LSOC) – A type of account that only holds positions and collateral associated with a single client in individually segregated accounts (ISEG), or multiple clients in legally segregated, operationally commingled accounts (LSOC). These types of accounts are assumed to be easier to port than non-segregated (omnibus) accounts.

  Sensitivity testing – The process of individually and jointly changing core assumptions underlying the stress test. Combining multiple sensitivities often represents a more severe test that goes beyond regulatory requirements and historical precedents.