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IMF Country Report No. 22/337

IRELAND

FINANCIAL SECTOR ASSESSMENT PROGRAM

TECHNICAL NOTE ON STRESS TESTING AND SYSTEMIC RISK ANALYSIS

November 2022

This paper on Ireland was prepared by a staff team of the International Monetary Fund as background documentation for the periodic consultation with the member country. It is based on the information available at the time it was completed on November 2, 2022.

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Title Page

IRELAND

FINANCIAL SECTOR ASSESSMENT PROGRAM

November 2, 2022

TECHNICAL NOTE

STRESS TESTING AND SYSTEMIC RISK ANALYSIS

Prepared By

Monetary and Capital Markets Department

Contents

• Glossary

• EXECUTIVE SUMMARY

• INTRODUCTION

• TOP-DOWN SOLVENCY STRESS TEST OF BANKS

• A. Solvency Stress Tests of the Banking Sector

• B. Macroeconomic Scenarios

• C. Banking Sector Vulnerabilities

• D. Methodology for Scenario-Based Solvency Stress Test

• E. Sensitivity Analysis of Retail and Large International Banks

• F. Sensitivity Analysis for Other International Banks

• BANK LIQUIDITY RISK ANALYSIS

• A. Introduction

• B. Liquid Assets and Funding Structure

• C. LCR-based Liquidity Stress Test

• D. Cashflow-based Liquidity Stress Test

• E. NSFR-based Liquidity Stress Test

• BANK INTERCONNECTEDNESS ANALYSIS

• A. Interbank and Intersectoral Network

• B. Domestic Interbank Contagion

• C. Bank – NBFI Interconnectedness

• D. Cross-border Interbank Contagion

• BANK CLIMATE STRESS TEST ANALYSIS

• A. Ireland Exposure to Climate Risks

• B. Transition Risk Sensitivity-based Stress Test

• C. Physical Risk Scenario-based Stress Test

• INSURANCE SECTOR SOLVENCY STRESS TEST

• A. Scope and Sample of the Solvency Stress Test

• B. Scenarios for the Solvency Stress Test

• C. Capital Standard and Modeling Assumptions

• D. Results of the Solvency Stress Test

• E. Sensitivity Analyses

• INSURANCE SECTOR LIQUIDITY RISK ANALYSIS

• A. Results of the Central Bank’s Liquidity Risk Analysis

• B. Analysis of Risks from Variation Margin Calls

• INSURANCE SECTOR CLIMATE RISK ANALYSIS

• A. Physical Risk

• B. Transition Risk

• INVESTMENT FUND LIQUITY STRESS TEST ANALYSIS

• A. Introduction

• B. Potential Spillovers from the Funds Sector

• C. Liquidity-Stress Testing Model

• INVESTMENT FUND STRESS TEST DESCRIPTIVE ANALYSIS

• A. Data and Sample Selection

• B. Portfolio Composition

• C. Redemption Shock

• INVESTMENT FUND STRESS TEST EMPIRICAL RESULTS

• A. Liquidity Resilience of Funds

• B. Liquidity Shortfall

• C. Conclusions of the Investment Fund Liquidity Stress Test Analysis

• FIGURES

• 1. Financial Sector Overview

• 2. Bank Liquidity and Capital Position

• 3. COVID-19 Pandemic-Related Payment Relief

• 4. Bank Profitability

• 5. Credit Quality of Lending Portfolios

• 6. Credit Quality of the CRE and SME Segments

• 7. Bank Funding Condition s

• 8. Bank Exposure to Climate Risks

• 9. Stress Testing Framework

• 10. ST Macroeconomic Scenarios

• 11. Sample Bank Balance Sheet Decomposition

• 12. Bank Credit Exposure and Quality by Geography and Segment

• 13. Loans by Stages

• 14. Loan Forbearance

• 15. Liability Composition

• 16. Sample Banks Securities Holdings

• 17. Structure of Solvency Stress Testing Framework

• 18. PD Projections

• 19. Use of PiT and TTC PDs for RWAs and Provisioning

• 20. Interest Rate Estimation by Portfolio

• 21. Take-up of Bank-facing COVID-19 Support Measures

• 22. Concentration Analysis

• 24. Methodology of Sensitivity Analysis for Other International Banks

• 25. Result of Sensitivity-Based Stress Test for Other International Banks

• 27. Bank Contractual Cashflows and Funding Profile

• 28. Liquidity Indicators

• 29. LCR Component

• 30. Results of the LCR-Based Stress Test

• 31. Counterbalancing Capacity

• 32. Asset Encumbrance

• 33. Results of the Cashflow-Based Stress Test

• 34. NSFR Development

• 35. Methodology – NSFR Stress Test

• 36. Results of the NSFR Stress Test

• 37. Interbank and Bank-NBFI Network

• 38. Total Assets of Financial Vehicle

• 39. Interconnectedness Analysis

• 40. Cross-Border Interconnectedness

• 41. Result for Cross-Border Interbank Contagion Analysis

• 42. Methodology – Transition Risks

• 44. Bank Capital Impact under Carbon Tax Shock

• 45. Bank Exposure to Transition Risk

• 46. Shock Calibration – Physical Risks

• 47. Physical Risk - Macroeconomic Scenario

• 48. Result of the Physical Risk Analysis

• 49. Components of Insurance Risk Analysis

• 50. Own Funds and Long-Term Guarantee Measures

• 51. Insurance Solvency ST—Valuation Impact

• 52. Insurance Solvency ST—Solvency Impact

• 53. Insurance Solvency ST—Sensitivity Analyses

• 54. Insurance Liquidity Risks

• 55. Insurers’ Variation Margin Calls

• 56. Insurers’ Physical Climate Risks—Natural Catastrophes

• 57. Insurers’ Physical Climate Risks—Parametric Approach

• 58. Insurers’ Sectoral Exposures

• 59. Insurers’ Transition Risks

• 60. Portfolio Composition of Irish-Domiciled Fixed-Income Funds

• 61. HQLA Buffers - Irish-domiciled Fixed-Income Funds

• 62. RCR and the Resilience of Funds

• 63. Liquidity Shortfall and RCR

• TABLES

• 1. Recommendations

• 2. The Banking System

• 3. PD Portfolio Mapping

• 4. Interest Rate Portfolio Mapping

• 5. Result of Scenario-Based Stress Test

• 6. LCR Stress Test Parameters

• 7. Cash Flow Based Stress Test Parameters

• 8. Estimation of Expected Default Frequency for Irish Firms

• 9. Projection of Corporate Balance Sheet and Vulnerability Indicators

• 10. Insurance Stress Test Specification

• 11. Investment Fund Data Availability in Morningstar

• 12. Sample of Investment Funds in the Stress Test

• 13. Liquidity Weights

• 14. Average Redemption Shocks for the ES and VaR Models

• APPENDICES

• I. Risk Assessment Matrix

• II. Housing Price Developments

• III The Estimation of the PD Satellite Models

• IV. The Estimation of the Interest Rate Satellite Models

• V. Shock Calibration of the Physial Risk Analysis of the Banking

• VI. Banking Sector Stress Testing Matrix (STeM)

• VI. Banking Sector Stress Testing Matrix (STeM)

• VII. Insurance Sector Stress Testing Matrix (STeM)

• VII. Insurance Sector Stress Testing Matrix (STeM)

• VIII. Investment Fund Liquidity Stress Testing Matrix (STeM)

• VIII. Investment Fund Liquidity Stress Testing Matrix (STeM)

• IX. Insurance Sector Interest Rate Scenarios

• X. Investment Fund Category Correspondence Table

• XI. RCR for a Range of Shock Scenarios

• XII. RCR and Liquidity Shortfall under the Heterogeneity Approach

• References

Glossary

Executive Summary¹

The FSAP took place against the background of a fast-evolving financial sector in Ireland and heightened uncertainty in the global economy. The Irish financial landscape has undergone significant changes since the global financial crisis with increasing divergence between an innovative and fast-growing international finance sector and the retail banking sector that has been consolidating and faces post-GFC operating restrictions and increasing competition from non-bank players. In the meantime, both the global pandemic and Brexit have left uneven marks across the economy, while there are risks from the unwinding of public support that has softened COVID-19 shock’s impact on the economy. Going forward, various ongoing and emerging risks, such as persistent inflationary pressures, fueled by supply bottlenecks, and the war in Ukraine, may impede recovery, and magnify vulnerabilities to downside shocks.

The banking sector weathered the pandemic with strong fundamentals, although pockets of vulnerabilities remain. While the pandemic was a significant shock to the economy, banks continued to maintain strong capital and liquidity buffers. Going forward, profitability challenges and long-term mortgage arrears by retail banks, high exposure to the CRE segment, and significant off-balance sheet exposures of large international banks may expose banks to both domestic and cross-border challenges.

Irish insurers also proved to be resilient during the COVID-19 pandemic, although the full effects have yet to be seen. Primary drivers of solvency ratios have been financial market valuations and interest rate movements affecting insurers’ investment portfolios and liability valuations. COVID-19 has led to spikes in claims on some non-life lines of business, most notably business interruption and event cancellation, which was partially offset by reductions in motor and liability claims. Life insurance claims for Irish exposures have been muted, reflecting the age profile of Covid deaths, but reinsurers with U.S. mortality exposure were more materially affected. Uncertainties remain as to how the pandemic and its aftermath will further impact the sector, particularly regarding: further market volatility and potential changes in investor sentiment, economic downside risks, “long COVID” effects on mortality and morbidity, and the impact of the pandemic on future lapse rates and premium income.

The FSAP conducted a comprehensive set of stress tests and risk analyses to assess the resilience and vulnerabilities of the banking, insurance, and investment fund sectors in Ireland. The banking analysis used scenario-based stress test to assess the resilience of retail and large international banks, while applying a streamlined sensitivity test on other international banks, which are all LSIs. The bank risk analysis also covered liquidity stress tests and contagion analysis, assessing domestic and cross-border interbank exposures, as well as domestic and cross-border cross-sectoral interlinkages between banks and non-bank financial institutions. The banking analysis included an assessment of climate change-related risks (both transition and physical) facing the sector. The insurance stress tests covered solvency, liquidity, and climate physical and transition risks. The analyses used both top down and bottom-up methodologies, with input from the (re)insurers. The stress testing analysis for investment funds assessed the liquidity resilience of the investment fund sector, focusing on potential liquidity mismatches when faced with severe, but plausible, redemption shocks.

The scenario-based bank solvency stress test confirmed the sector’s resilience to severe macroeconomic shocks, while revealing pockets of vulnerabilities as the economy is exiting from pandemic-related policy support.

• The baseline scenario confirms banks’ strong capital positions, with further capital accumulation. Both retail and large international banks would see their fully loaded CET1 ratios trending upwards, from 16.4 percent to 17.8 percent for retail banks and from 19.9 percent to 27.9 percent for large international banks, with no banks falling below the hurdle rates.² The slower accumulation of capital for retail banks, relative to large international banks, reflects their lower pre-provision income, driven by their limited income generation capacity.

• The adverse scenario confirms banks’ resilience to severe yet plausible adverse shocks. Although the adverse scenario produced a significant impact on bank capital ratios, no bank saw its capital ratios fall below the hurdle rates, owing to the high initial capital positions of both retail and large international banks, as well as the high pre-provision income of the large international banks. On aggregate, the fully loaded CET1 ratio declines by about 6.7 percentage points for retail banks and 0.4 percentage points for large international banks by the 5th year. When looking at the trough, however, capital depletion can reach 7.2 and 2.3 percentage points for retail and large international banks, respectively. Among risk factors considered³, credit risk provisioning is by far the largest contributor to the decline in capital ratios, with the cumulative effect amounting to 7.4 percentage points over five years.

The bank stress test results paint a slightly more adverse picture when assuming an additional impact from the unwinding of pandemic support policies. To address the uncertainties surrounding the impact on portfolios that have benefitted from payment breaks, and broad policy support during the pandemic, the FSAP carried out a separate sensitivity analysis. The analysis assumed that 50 percent of loans with either active or expired moratoria deteriorate from stage one and two assets into stage three assets, which resulted in one retail bank’s CET1 and Tier 1 ratio falling below the hurdle rates under the adverse scenario, with the capital shortfall against the CET1 hurdle rate amounting to 0.2 percent of GDP.

The LCR-based stress test suggests that banks are resilient to adverse liquidity conditions. On aggregate, banks saw a meaningful decline of their LCR ratios across stress scenarios, with retail banks experiencing a larger impact under the retail scenario and international banks facing higher stress under the wholesale scenario. All banks are able to withstand the most severe shock within the 30-day window, underpinned by a high initial level of liquidity buffers, which rose further during the pandemic.

The bank cashflow-based stress test indicates potential liquidity gaps when extending the analysis beyond 30-days. Banks are broadly resilient against liquidity outflows thanks to their existing counterbalancing capacities in the short-term. However, their liquidity position becomes weaker beyond three months owing to a maturity mismatch characterized by more frontloaded cash outflows and backloaded cash inflows. Large international banks are more prone to liquidity shortfalls even in the short-term, due to their high share of wholesale funding⁴ and larger off-balance sheet exposures, which highlights the importance of regular monitoring of large off-balance sheet exposures.^5,6

Both the LCR and cashflow-based stress tests focusing on major foreign currencies reveal some vulnerabilities to U.S. dollar and U.K. Sterling denominated outflows. The same LCR and cashflow-based exercises were applied to significant foreign currencies of the banks, even though there is no regulatory minimum currency-specific liquidity requirement at present. The results indicate vulnerabilities across currencies, particularly for international banks in U.S. dollars. This can be explained by various factors, such as weaker initial positions, non-trivial off-balance sheet exposures,⁷ as well as high reliance of international subsidiaries on foreign currency backstop from their foreign parents.

The interconnectedness analysis, which covers interbank, bank-NBFI and cross-border contagion risks, identified significant linkages of the large international banks with cross-border banks and NBFIs. While interbank linkages appear to be muted both for the domestic and the cross-border interbank market, the network results points to a high degree of connectivity between large international banks and NBFIs, accounting for 45 percent of the total exposures of the large international banks. The inward spillover risks of the large international banks become much more pronounced when adding the top NBFIs by exposure size into the network, suggesting larger vulnerability of large international banks to shocks from NBFIs

Banking sector climate risk analysis studied the relevance of both transition and physical risks facing the banking sector. For transition risks, the FSAP first carried out a single factor analysis simulating carbon-tax shocks, which revealed a meaningful impact on Irish corporates, with energy-intensive sectors experiencing the largest PD increases. Then, the direct impact on the banking sector was studied to gauge the solvency implications of higher default frequencies driven by the carbon-tax shock, which leads to notable CET1 capital depletion of up to 3.5 percentage points (or 15 percent of existing CET1 capital) under the most severe scenario. The evolution of the impact over the risk horizon also confirms important non-linear effects of carbon taxation on corporate financial health, which warrants a speedy transitioning to greener technology to ensure business viability for carbon-intensive sectors.

The physical risk analysis showed important linkages between domestic physical hazards and bank financial health going forward. Simulating a severe flooding event and applying the same methodology used in the scenario-based stress test, the analysis produced a non-trivial depletion of bank CET1 capital (around 2.4 percentage points) at trough, before recovering to close to pre-shock levels. This non-trivial depletion suggests the need for enhanced monitoring of banking sector exposure to climate sensitive sectors and precautionary action (e.g., ensure loans are secured with high quality collateral or insured against physical damage) to mitigate climate-related risks to financial stability.

The insurance sector ST analysis focused on market and credit risks and showed an overall broad resilience of insurers against the adverse scenario. The ST analysis followed a top-down approach and covered 25 (re)insurers, or more than 70 percent of the market in each sub-sector (life, non-life, and reinsurance). The vast majority of insurers remain well-capitalized, but one insurer would not be able to meet the solvency capital requirement (SCR) following the stress, taking no reactive management actions into account—although the capital shortfall would amount to less than €10 million. Non-life insurers are affected most from the shocks, while several life insurers in the sample benefit from a higher Volatility Adjustment (VA). The coverage of the SCR decreases by 13 percentage points for the median non-life insurer. The median post-stress SCR ratio in the life sector is 6 percentage points higher than pre-stress—however, this overstates the impact on the sector, as the SCR ratio declines for the majority of life insurers.

Most of the decline in asset values for insurers stems from higher corporate and sovereign spreads, while equity and property shocks have a more muted impact. Higher interest rates and the depreciation of the Euro offset other adverse shocks as most insurers in the sample have a slight excess of foreign-denominated assets compared to their liabilities, resulting in a net valuation gain. These combined declines in asset values cannot be fully compensated by lower liabilities (mainly due to higher discount rates).

A liquidity shock is unlikely to have a systemic impact on the insurance sector, in fact, the central bank’s bottom-up analysis indicates that results are very much driven by company specifics. The relatively small sample of only ten insurers does not reveal vulnerabilities at the sector level. On aggregate, the share of liquid assets is relatively high, and the sum of inflows even increases in the adverse scenario (compared to the baseline) as a result of its impact on the direction of derivative-related collateral flows at some firms. This, however, is unlikely to be a sector-wide phenomenon given the limited use of derivatives across the entire market. Additionally, the FSAP’s top-down analysis of risks from margin calls for interest rate swaps confirms the low vulnerabilities stemming from this channel, albeit reporting data for other derivative types is incomplete. The results underline the importance for the supervisor to understand liquidity flows and liquidity risk management practices, which also needs to include the insurance group structures.

The insurance sector is exposed to climate risks mainly through its non-life underwriting. The FSAP analysis indicates that even large natural catastrophes, when seen in isolation, would likely not have a pronounced impact on solvency levels. Domestically, the most important natural perils are windstorms, floods, and freezes, but many Irish (re)insurers underwrite business globally, exposing them also to other types of international climate-related risks, such as U.S. hurricanes or wildfires. The impact of a major windstorm in Ireland and the United Kingdom would be seen mostly on profits, and SCR ratios would decline, on average, by less than 3 percentage points. However, modeling challenges regarding physical risks persist, and Irish insurers rely heavily on intra-group reinsurance.

The impact of transition risk overall is manageable, but larger for life insurers, mainly due to a comparably riskier asset allocation⁸—however, results come with considerable modelling uncertainties. Transition risks were analyzed via a top-down approach, assuming that the effect of the NGFS scenario of an orderly 1.5 degree increase until 2050, is priced by investors instantaneously. A lower valuation could be expected particularly for equity investments, while bond valuations and default rates are expected to be more stable. In absolute amounts, asset values could decline by around €7 billion (or 2.3 percent of total investment assets).

The stress tests for investment funds indicate that the sector is generally resilient to redemption shocks, but pockets of vulnerability exist. Resilience is measured here in terms of ability to meet large redemption requests in a stressed market, without the use of liquidity management tools or the sale of less liquid assets. Most fixed-income investment funds in Ireland, which are the focus of the liquidity stress test, would be able to weather severe but plausible redemption shocks under a wide range of shock scenarios. However, certain categories of funds, including high-yield bond funds and emerging-market focused fixed-income funds, which are more susceptible to liquidity mismatch, may be less resilient to severe market stress.

Ireland has made good progress in implementing the recommendations from the 2016 FSAP on stress-testing of investment funds, but some work remains. The central bank has made significant strides in building a stress-testing framework for funds based on recommendations in the 2016 FSAP, but the model remains a work-in-progress. Given the size, accelerating growth, and systemic importance of the investment fund sector, the central bank should reinforce its efforts in completing the model and simulations and conducting regular stress tests of Irish-domiciled funds.

Table 1.

Ireland: Recommendations

^*C = Continuous; I = Immediate (within one year); ST = Short Term (within 1-3 years); MT = Medium Term (within 3-5 years).

^**H = High; M = Medium; L = Low.

Table 1.

Ireland: Recommendations

Recommendation	Addressee	Timing*	Priority**
Banking – Risk Analysis
1. Continue to closely monitor portfolios that benefited from pandemic payment breaks and broader policy support, including other forms of forbearance measures to ensure banking sector resilience with the phase-out of pandemic supportive policies. (¶3, ¶48)	CBI	C	H
2. Continue to regularly perform liquidity stress tests by individual bank and significant foreign currencies to identify and provide early warning signals to banks with liquidity gaps over short and long-term horizons. (¶66, ¶76)	CBI	C	H
3. Continue to regularly monitor large off-balance sheet exposures (via credit and liquidity facilities). Provide early warning signals to banks with associated liquidity risks. (¶58, ¶75)	CBI	C	H
4. Expand data collection on interbank and bank-NBFI exposures at entity level (in addition to existing large exposure dataset) to complete interbank and bank-NBFI network analysis. (¶85, ¶93)	CBI	MT	H
5. Analyze the riskiness of banks-NBFI linkages and their direct and indirect impact on the banking sector, with a particular focus on international banks. (¶81, ¶94)	CBI	ST	H
6.Initiate data collection on banking exposures to both transition and physical climate risks, such as bank specific carbon exposures as well as leveraging geospatial data to assess exposures to corporate and mortgage borrowers facing high flooding risks, to allow in-depth analysis on climate related risks to financial stability. (¶110, ¶111, ¶112, ¶120)	CBI	MT	M
7. Develop models to properly assess the impact of transition and physical climate risks on the banking sector. (¶110, ¶111, ¶112, ¶120)	CBI	MT	M
Insurance – Oversight
8. Continue strengthening the supervision of intra-group transactions and concentrations, with a focus on post-Brexit group structures, recovery planning, and liquidity risk management. (¶142, ¶152)	CBI	ST	H
Insurance – Risk Analysis
9. Conduct regular top-down solvency stress tests of insurers, also to validate scenarios and assumptions used by insurers in their recovery plans. (¶138)	CBI	ST	M
10. Monitor protection gaps at regional and local level, including price dynamics and the cost of insurance, and consider options to narrow protection gaps wherever material, particularly with respect to flood risks. (¶155)	DoF, CBI	MT	M
Investment Fund – Risk Analysis
11. Complete the internal stress-testing framework for investment funds and money market funds. (¶191)	CBI	MT	H
12. Determine the common asset holdings of investment funds, banks, and relevant non-banks. (¶192)	CBI, CSO	MT	M
13. As part of the ongoing policy development on IF liquidity risk management and taking into account developments at the EU and international level, review the use of liquidity management tools by IFs, with a particular focus on funds that have demonstrated liquidity challenges in recent periods of stress. (¶193)	CBI	ST	H

^*C = Continuous; I = Immediate (within one year); ST = Short Term (within 1-3 years); MT = Medium Term (within 3-5 years).

^**H = High; M = Medium; L = Low.

View Table

Table 1.

Ireland: Recommendations

Recommendation	Addressee	Timing*	Priority**
Banking – Risk Analysis
1. Continue to closely monitor portfolios that benefited from pandemic payment breaks and broader policy support, including other forms of forbearance measures to ensure banking sector resilience with the phase-out of pandemic supportive policies. (¶3, ¶48)	CBI	C	H
2. Continue to regularly perform liquidity stress tests by individual bank and significant foreign currencies to identify and provide early warning signals to banks with liquidity gaps over short and long-term horizons. (¶66, ¶76)	CBI	C	H
3. Continue to regularly monitor large off-balance sheet exposures (via credit and liquidity facilities). Provide early warning signals to banks with associated liquidity risks. (¶58, ¶75)	CBI	C	H
4. Expand data collection on interbank and bank-NBFI exposures at entity level (in addition to existing large exposure dataset) to complete interbank and bank-NBFI network analysis. (¶85, ¶93)	CBI	MT	H
5. Analyze the riskiness of banks-NBFI linkages and their direct and indirect impact on the banking sector, with a particular focus on international banks. (¶81, ¶94)	CBI	ST	H
6.Initiate data collection on banking exposures to both transition and physical climate risks, such as bank specific carbon exposures as well as leveraging geospatial data to assess exposures to corporate and mortgage borrowers facing high flooding risks, to allow in-depth analysis on climate related risks to financial stability. (¶110, ¶111, ¶112, ¶120)	CBI	MT	M
7. Develop models to properly assess the impact of transition and physical climate risks on the banking sector. (¶110, ¶111, ¶112, ¶120)	CBI	MT	M
Insurance – Oversight
8. Continue strengthening the supervision of intra-group transactions and concentrations, with a focus on post-Brexit group structures, recovery planning, and liquidity risk management. (¶142, ¶152)	CBI	ST	H
Insurance – Risk Analysis
9. Conduct regular top-down solvency stress tests of insurers, also to validate scenarios and assumptions used by insurers in their recovery plans. (¶138)	CBI	ST	M
10. Monitor protection gaps at regional and local level, including price dynamics and the cost of insurance, and consider options to narrow protection gaps wherever material, particularly with respect to flood risks. (¶155)	DoF, CBI	MT	M
Investment Fund – Risk Analysis
11. Complete the internal stress-testing framework for investment funds and money market funds. (¶191)	CBI	MT	H
12. Determine the common asset holdings of investment funds, banks, and relevant non-banks. (¶192)	CBI, CSO	MT	M
13. As part of the ongoing policy development on IF liquidity risk management and taking into account developments at the EU and international level, review the use of liquidity management tools by IFs, with a particular focus on funds that have demonstrated liquidity challenges in recent periods of stress. (¶193)	CBI	ST	H

^*C = Continuous; I = Immediate (within one year); ST = Short Term (within 1-3 years); MT = Medium Term (within 3-5 years).

^**H = High; M = Medium; L = Low.