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### Executive Summary — Structural changes and emerging risks
- NBFIs and market-based finance have become more prominent since the Global Financial Crisis (GFC), increasing the importance of systemic liquidity stress alongside traditional bank-focused solvency concerns.
- Key drivers of heightened market-driven liquidity risks in NBFIs:
  - leverage, maturity mismatches, derivatives exposures, and reliance on repo funding.
  - centralized clearing and margining shifting some solvency risks into liquidity risks.
  - global asset managers transmitting external shocks through volatile capital flows, linking domestic financial stability to external and foreign exchange liquidity conditions.
- Recent illustrative episodes:
  - the “dash for cash”.
  - the 2022 stress episode involving NBFIs with liability-driven investment (LDI) strategies.
- Common propagation mechanisms across NBFIs and banks: margin and collateral calls, investor redemptions, and fire sales.

### Executive Summary — Need for a systemwide perspective
- Traditional stress testing often focuses on single-sector vulnerabilities (banks, insurers, investment funds) and bank-network contagion; this misses cross-sectoral and cross-border amplification channels.
- FSB and sectoral SSBs emphasize systemwide assessments to monitor risks and guide policy.
- Authorities have pursued two complementary approaches:
  - experimental top-down models using supervisory data (common in IMF exercises).
  - bottom-up exercises in collaboration with private-sector participants.

### Executive Summary — Data, technical, and operational constraints
- Significant constraints:
  - limited data availability for lightly regulated NBFIs, off-balance-sheet exposures, and cross-border transactions.
  - need for transaction-level data to capture derivatives, repos, and lightly regulated NBFIs’ positions.
  - behavioral responses to liquidity shocks are complex, context dependent, and hard to model.
  - integrating bottom-up exercise results consistently across diverse environments is not straightforward.
  - resource, data management, and coordination demands increase with expanded model coverage and confidentiality needs.

### Executive Summary — IMF’s generic systemwide analysis tools
- Two tools developed:
  - Excel-Based Systemwide Liquidity Analysis Tool:
    - leverages sector-aggregate flow-of-funds data to monitor liquidity shocks and transmission across domestic financial linkages.
    - suitable for a broad range of economies, including some low-income countries, given available data.
  - Market Impact from Investment Funds Liquidity Distress (MILD) framework:
    - uses granular investment funds and their asset data to assess redemption pressures, asset sales, and secondary price effects.
- Tools are adaptable for FSAPs and often augmented for country-specific data and priorities.

### Executive Summary — FSAP applications, findings, and enhancements
- Early FSAP efforts targeted EMDEs where external shocks, volatile capital flows, and FX liquidity constraints drive systemic risk.
- Common empirical findings:
  - nonfinancial entities (corporates, households, or public sector) often play major roles in transmitting or triggering systemic liquidity stress.
  - advanced-economy FSAPs showed liquidity stress can rapidly spread across banks, insurers, money market funds, and core funding markets even without significant solvency losses.
- Methodological features:
  - exploration of a range of behavioral scenarios to identify actors and actions likely to drive or mitigate systemic risk.
  - attention to systemwide consistency of client money withdrawals or redemptions (domestic retention vs exit), including macroeconomic channels involving exchange rate and capital flows.
- Enhancements in advanced-economy cases:
  - integration of various NBFI segments, fire-sale price effects, and liquidity needs from repos and derivatives using transaction-level data.
- Repeated outcome: identification of critical data gaps to improve future analysis and policy design.

### Executive Summary — Way forward and near-term priorities
- Leverage currently available but underutilized data reported to national regulators (e.g., banks’ granular counterparty credit and large exposure information).
- Deeper integration of market microstructure, margining, and clearing arrangements into stress scenarios using FMI transaction-level data, as in the 2025 Euro Area FSAP.
  - managing these data is resource-intensive and confidentiality provisions often exceed those for standard macro scenario stress tests; close collaboration with national authorities and key FMIs is crucial.
- Over time, incorporate insights from bottom-up exercises and behavioral evidence to support more sophisticated behavioral modeling approaches, including agent-based frameworks.
- Continued international efforts to address data gaps and more systematic data-sharing and coordination across national authorities.

### Executive Summary — Role and limits of systemwide stress testing
- Systemwide stress testing:
  - not designed to deliver precise assessments of system resilience.
  - effective at identifying potential weak links, critical data gaps, policy trade-offs, and regulatory features that may strengthen individual sectors while increasing system-wide fragility.
- As financial systems trend toward greater market-based intermediation, systemwide approaches will remain central to understanding and mitigating systemic risks.

### Introduction — Macro and sectoral context
- Of over $500 trillion in global financial assets, NBFIs now hold $256 trillion (FSB, 2025).
- NBFIs have traditionally comprised about half of total system assets; banks’ share has gradually receded since the GFC.
- “Other financial institutions” (OFIs) expansion driven by asset management (MMFs, hedge funds, and other investment funds).
- Market-structure shifts:
  - Short-term funding markets shifted toward sovereign repos and derivatives accessible by banks and NBFIs alike.
  - Open-end funds face liquidity stress from NAV declines prompting redemptions, cash buffer depletion, or fire-sale assets (“dash-for-cash”).
  - Funds with derivatives or repo exposures face urgent collateral or cash needs due to margin calls.
- Insurance and pension sectors’ increased integration with asset management raises exposure to leverage, liquidity mismatches, and valuation uncertainty (example: LDI stresses in UK pension funds in 2022).

### Introduction — Systemic liquidity stress and interconnectedness
- Systemic liquidity events arise when numerous institutions experience liquidity strains simultaneously; market valuation shocks can trigger and propagate such stress via interconnections.
- Amplification channels include leverage (including off-balance-sheet contracts), counterparty credit risk, and funding risk.
- Examples and metrics:
  - Margin calls can rapidly drain liquidity; the collapse of Archegos in 2021 inflicted more than $10bn in losses on banks via leveraged, concentrated, opaque investments.
  - In early 2025, trade tensions caused large swings across equity, bond, and commodity markets, generating significant margin calls.
- Cross-exposures are widespread; in the US and Europe some large banks have NBFI exposures exceeding their Tier 1 capital.
- Flow-of-funds statistics capture balance-sheet linkages, but off-balance-sheet exposures (derivatives, repos) can further increase interconnectedness.
- Cross-border portfolio investments channel global liquidity cycles into EMDEs; shocks can hit equity and bond markets, then ripple into domestic systems via local dash-for-cash behavior and exchange-rate effects.
- FX liquidity risk: large capital outflows raise demand for hard-currency FX liquidity and can lead to bank FX shortages or sharp currency depreciation; central banks’ FX backstop capacity is limited by international reserves.

### Introduction — Need for a systemwide perspective and literature
- Definition: systemwide analysis considers multiple key sectors, capturing direct (cross-exposures) and indirect (common exposures, firesale price dynamics, margin calls) contagion effects.
- IMF use: applied in FSAPs and technical assistance for nearly a decade; bilateral exercises often rely on confidential country-specific data and cover broad sectors including nonfinancial sectors when relevant.
- Theoretical foundations and post-GFC amplification mechanisms include runs on repos, collateral channels, fire sales, interplay of market and funding liquidity, leverage cycles, and cash hoarding/network effects.
- Recent advances emphasize margin and collateral call dynamics, central clearing complexities, and CCPs as liquidity transformers; margin procyclicality can exacerbate interbank hoarding and fragility.

### Introduction — Empirical and operational assessment and data landscape
- Regulatory data: granular confidential data for banks and insurers; security-level holdings, NAVs, and flows publicly available for many investment funds; sparse supervisory/public data for hedge funds and private family offices.
- FMI transaction-level data exist but are resource-intensive to process.
- Quantitative approaches:
  - Banking contagion models exploit supervisory interbank matrices and network methods (Eisenberg–Noe lineage).
  - Investment fund stress tests follow: (1) market shocks reduce NAVs, (2) redemptions rise, (3) asset sales create price impacts driving further NAV reductions.
  - CCP stress tests focus on member default and CCP resilience but often do not assess systemwide resilience including members’ clients or leveraged positions.
- Regulatory data summary (GFA = global financial assets):
  - Investment funds (excluding MMFs and hedge funds): $58 trillion, 12% of GFA.
  - Insurance: $40 trillion, 9% of GFA.
  - Pension funds: $43 trillion, 9% of GFA.
  - Money market funds: $8.5 trillion, 2% of GFA.
  - Structured finance vehicles: $6 trillion, 1% of GFA.
  - Hedge funds: $6 trillion, 1% of GFA.
  - Central counterparties: $0.7 trillion, 0.1% of GFA.

### Introduction — IMF’s systemwide analysis tools (details)
- Two standardized tools:
  - Excel-based systemwide liquidity analysis tool (Balance Sheet Approach / BSA using sector-aggregate flow-of-funds by counterpart).
  - MILD — Market Impact from Investment Funds Liquidity Distress.
- Purpose: parsimonious, top-down tools that identify amplification channels, systemic sectors, market spillovers, and data gaps; support sectoral stress test interpretation and policy discussions.

### Excel-Based Systemwide Liquidity Analysis Tool — Key features
- Uses sector-aggregate flow-of-funds data by sector, counterparty, and instrument.
- Runs cash-flow-based liquidity stress tests across systemically important sectors with cross-sectoral consistency.
- Captures liquidity stress transmission (e.g., investment fund redemptions withdrawing bank deposits transfer stress to banks).
- Highlights reinvestment destination importance (domestic banks vs assets outside domestic system).
- Effective for linking financial stability with external vulnerability in EMDEs and small open economies; emphasizes central bank international reserves under FX liquidity stress.
- Results sensitive to behavioral assumptions and liquidation order; multiple scenario and sensitivity analyses recommended.

### MILD — Core components and limitations
- Modular, scenario-based framework built on granular fund- and asset-level data.
- Core components:
  - Redemption shocks calibrated using parametric assumptions, historical flows, or flow-performance relationships.
  - Optional market shocks to asset valuations.
  - Modeling of asset liquidity, liquidation pecking orders, and mitigating actions (e.g., short-term repo borrowing).
- Mechanism: translate funds’ liquidity demand into asset sales under different behavioral assumptions (waterfall, pro-rata, mixed), then apply market impact functions to map sales volumes into price declines by asset segment.
- Outputs: liquidity shortfalls, assets sold, market price impact, and losses to funds and other sectors presented as distributions across scenarios.
- Limitations:
  - Partial-equilibrium framework—not full systemwide consistency or general-equilibrium dynamics.
  - Does not track reinvestment of redeemed funds.
  - Sensitive to behavioral assumptions, liquidation strategies, and market depth parameters.
  - Intended as scenario-based indicators of vulnerability and amplification, not point forecasts.

### FSAP Applications — Country examples and findings
- Common methodology: top-down, scenario-based approaches tailored to jurisdiction-specific vulnerabilities and data availability; estimate liquidity needs and trace direct/indirect spillovers under alternative behavioral assumptions.
- Early applications: Luxembourg (2017), Andorra, Mauritius, Sweden (Article IVs), Armenia (2018).
- Illustrative country findings and recommendations:
  - Low-income country: public finance stress, FX deposit runs, and foreign investor exits; allow banks to satisfy FX-dedicated reserve requirements in hard currency and hold global safe assets if FX LCR is introduced.
  - Emerging market: capital outflow shocks transmit across sectors; NFCs can be highly vulnerable; central bank may adjust FX reserve requirement ratio to increase usable FX buffers.
  - High-income commodity exporter: introduce contingent flexibility in reserve backing and consider FX LCR and preemptive prudential measures.
- Selected country cases:
  - Philippines (2021): NFCs can be systemically important due to liquidity positions outside prudential perimeter.
  - Chile (2021): recommended improving pension fund regulation, mutual fund liquidity management, bank liquidity stress tests, interbank repo development, and central bank collateral/ELA framework.
  - Türkiye (2023): FX liquidity risks with high inflation (~80 percent in mid-2022) and deposit dollarization; central bank–bank nexus showed FX assets held at central bank about double readily available FX gross international reserves in mid-2022; tests indicated banks withstand moderate FX stress but severe outflows could drain reserves.
  - Iceland (2023): central bank had sufficient reserves partly due to boosting gross international reserves with external borrowing (more than 40 percent of gross international reserves funded by external borrowing).
  - India (2024): NBFCs’ reliance on wholesale funding and bond funds; CDMDF provides liquidity backstop but not sufficient for all pressures; India’s relatively closed capital account means stress redistributes liquidity rather than producing aggregate FX shortages.
  - Mexico (2022): enhanced tool to assess capital outflows from local sovereign bond market using granular BSA data; stress scenarios showed banks’ central role in system liquidity backstopping and development banks’ vulnerabilities.
  - Euro Area: incorporated margin calls from derivatives and collateral calls from repos, transaction-level supervisory data; modeled immediate (two-day) vs short-term (two-week) dynamics given T+2 settlement; highlighted MMFs’ pivotal amplifying role and significant second-round effects.
  - United States (2020 FSAP): mutual fund asset liquidations could significantly price-impact EM and high-yield bonds; results sensitive to market behaviors and price-impact estimation.

### FSAP Experience — Key takeaways
- Tailor systemwide liquidity analysis to jurisdictional financial structure, vulnerabilities, and data availability.
- Common patterns:
  - Excel-based BSA useful in less complex, externally exposed economies to trace capital outflows, FX pressure, and nonfinancial sector propagation.
  - Advanced market-based systems require focus on bank–NBFI linkages, common exposures, fire-sale dynamics, and repo/derivatives margin and collateral calls.
- Limitations and sensitivities:
  - Results highly sensitive to behavioral assumptions, fire-sale price-dynamics calibration, perimeter of covered institutions/instruments, and scenarios considered.
  - Most exercises identify transmission channels, systemic actors, data gaps, safety nets, and analytical priorities rather than issuing pass/fail thresholds.
  - “Soft” recommendations (methodological advances, stronger supervision, data gaps closure) predominate.

### Way Forward — Data, behavior, and methodological challenges
- Data gaps primary constraint: need cross-sectoral interconnectedness data; missing off-balance-sheet items, cross-border transactions concentrated in tax havens, and activity-level FMI data.
- Near-term approaches to fill data gaps:
  - Use confidential counterparty data from regulated entities to map significant NBFI activities and concentrated exposures.
  - Leverage FMI transaction-level data to monitor margin and collateral calls under stress.
  - Greater collaboration with national authorities due to confidentiality and data-processing burdens.
- Behavioral uncertainty:
  - Agents’ responses are complex, time-varying, and psychology-driven; systemwide exercises therefore explore a range of behavioral assumptions and rely on expert judgment.
  - Bottom-up exercises (e.g., BoE SWES) reveal realistic behavioral patterns that inform advanced models, including agent-based models (ABMs).
- Market microstructure and clearing arrangements materially affect stress propagation: margin formulas, settlement cycles (T+2), CCP opacity, and bilateral vs centrally cleared trades.
- Consistency in agent actions is crucial: reinvestment behavior matters; precautionary liquidity hoarding by otherwise resilient banks can amplify contagion.
- Technical estimation challenges: estimating sale-price dynamics in illiquid markets is difficult; volatility-based price-impact methods can yield counterintuitive results in low-trade markets; equilibrium approaches may be more reliable where trading is sparse.
- Recommended combined approach: continue combining top-down tools (Excel-based BSA, MILD), bottom-up exercises, FMI data use, and behavioral insights while expanding data collection and inter-agency collaboration.

### Conclusion — Progress, gaps, and policy relevance
- IMF has advanced top-down systemwide risk analysis over the past decade; approach is crucial for assessing systemic risks from NBFIs and their spillovers.
- Recent work focused more on NBFIs, market finance, and liquidity risks from margin and collateral calls, aligning with FSB initiatives (FSB, 2024b).
- Evaluations will increasingly depend on transaction-level FMI data supplemented by partial entity or counterparty data from regulated institutions and bottom-up exercises.
- These methods demand significant resources and close, ongoing collaboration with national authorities; multi-year engagement may be required beyond FSAP timelines.
- Specific analytical gaps: deeper understanding needed of risks associated with hedge fund basis trades financed through repo transactions amid rising public debt in core markets (see BIS Quarterly Bulletin, December 2025, and the October 2024 GFSR).
- Uses and limits:
  - Systemwide risk analysis is usually not suited to draw strong conclusions about system resilience to shocks.
  - Useful for identifying potential weak links, critical data gaps, priorities for supervisory and reporting frameworks, areas for improving data sharing and cross-agency coordination, and regulatory features that might trade off sectoral resilience for system fragility (e.g., margin practices).

*Source: wpiea2026170-source-pdf*

### Executive Summary ......................................................................................................

### Executive Summary

### Structural changes and emerging risks
- NBFIs and market-based finance have become more prominent since the Global Financial Crisis (GFC), increasing the importance of systemic liquidity stress alongside traditional bank-focused solvency concerns.
- Key drivers of heightened market-driven liquidity risks in NBFIs:
  - leverage, maturity mismatches, derivatives exposures, and reliance on repo funding.
  - centralized clearing and margining shifting some solvency risks into liquidity risks.
  - global asset managers transmitting external shocks through volatile capital flows, linking domestic financial stability to external and foreign exchange liquidity conditions.
- Recent illustrative episodes:
  - the “dash for cash”.
  - the 2022 stress episode involving NBFIs with liability-driven investment (LDI) strategies.
- Common propagation mechanisms across NBFIs and banks: margin and collateral calls, investor redemptions, and fire sales.

### Need for a systemwide perspective
- Traditional stress testing often focuses on single-sector vulnerabilities (banks, insurers, investment funds) and bank-network contagion; this misses cross-sectoral and cross-border amplification channels.
- The Financial Stability Board (FSB) and sectoral Standard Setting Bodies (SSBs) emphasize systemwide assessments to monitor risks and guide policy.
- Authorities have pursued two complementary approaches:
  - experimental top-down models using supervisory data (common in IMF exercises).
  - bottom-up exercises in collaboration with private-sector participants.

### Data, technical, and operational constraints
- Significant constraints hinder systemwide stress testing:
  - limited data availability for lightly regulated NBFIs, off-balance-sheet exposures, and cross-border transactions.
  - need for transaction-level data to capture derivatives, repos, and lightly regulated NBFIs’ positions.
  - behavioral responses to liquidity shocks are complex, context dependent, and hard to model.
  - integrating bottom-up exercise results consistently across diverse environments is not straightforward.
  - resource, data management, and coordination demands increase with expanded model coverage and confidentiality needs.

### IMF’s generic systemwide analysis tools
- Two IMF tools developed over nearly a decade:
  - Excel-Based Systemwide Liquidity Analysis Tool:
    - leverages sector-aggregate flow-of-funds data to monitor liquidity shocks and transmission across domestic financial linkages.
    - suitable for a broad range of economies, including some low-income countries, given available data.
  - Market Impact from Investment Funds Liquidity Distress (MILD) framework:
    - uses granular investment funds and their asset data to assess redemption pressures, asset sales, and secondary price effects.
- Tools are adaptable for FSAPs and often augmented for country-specific data and priorities.

### FSAP applications, findings, and enhancements
- Early FSAP efforts focused on emerging and developing economies where external shocks, volatile capital flows, and FX liquidity constraints drive systemic risk.
- Common empirical findings:
  - nonfinancial entities (corporates, households, or public sector) often play major roles in transmitting or triggering systemic liquidity stress.
  - advanced-economy FSAPs showed liquidity stress can rapidly spread across banks, insurers, money market funds, and core funding markets even without significant solvency losses.
- Methodological features of FSAP exercises:
  - exploration of a range of behavioral scenarios to identify actors and actions likely to drive or mitigate systemic risk.
  - careful discussion of systemwide consistency of client money withdrawals or redemptions (domestic retention vs exit), including macroeconomic channels involving exchange rate and capital flows—an area national authorities’ exercises typically do not account for.
- Enhancements in advanced-economy cases:
  - integration of various NBFI segments, fire-sale price effects, and liquidity needs from repos and derivatives using transaction-level data.
- Repeated outcome: identification of critical data gaps to improve future analysis and policy design.

### Way forward and near-term priorities
- Leverage currently available but underutilized data reported to national regulators—examples include banks’ granular counterparty credit and large exposure information—to better measure linkages with NBFIs and identify risk concentrations.
- Deeper integration of market microstructure, margining, and clearing arrangements into stress scenarios by utilizing transaction-level data collected by financial market infrastructures (FMIs), as demonstrated in the 2025 Euro Area FSAP.
  - recognizing that managing these data is resource-intensive and confidentiality provisions often exceed those for standard macro scenario stress tests; close collaboration with national authorities and key FMIs is crucial.
- Over time, incorporate insights from bottom-up exercises and behavioral evidence to support more sophisticated behavioral modeling approaches, including agent-based frameworks.
- Continued international efforts to address data gaps and more systematic data-sharing and coordination across national authorities will facilitate better use of existing data sources.

### Role and limits of systemwide stress testing
- Systemwide stress testing is a valuable addition to the financial stability toolkit despite current limitations:
  - not designed to deliver precise assessments of system resilience.
  - effective at identifying potential weak links, critical data gaps, policy trade-offs, and regulatory features that may strengthen individual sectors while increasing system-wide fragility.
- As financial systems trend toward greater market-based intermediation, systemwide approaches will remain central to understanding and mitigating systemic risks.

*Executive Summary, IMF Working Paper*

### Introduction

### Introduction

### The Rising Prominence of Nonbank Financial Institutions (NBFIs)
- Of over $500 trillion in global financial assets, NBFIs now hold $256 trillion (FSB, 2025).
- NBFIs have traditionally comprised about half of total system assets; banks’ share has gradually receded since the Global Financial Crisis (GFC).
- Structural change: “other financial institutions” (OFIs)—NBFIs excluding pension funds, insurers, and financial auxiliaries—have rapidly expanded, propelled by the asset management industry (MMFs, hedge funds, and other investment funds).
- Market-structure shifts:
  - Short-term funding markets moved away from unsecured interbank lending toward sovereign repos and derivatives accessible by banks and NBFIs alike.
  - Open-end funds face liquidity stress from NAV declines prompting redemptions, causing managers to run down cash buffers or fire-sale assets (“dash-for-cash”).
  - Funds with derivatives or repo exposures may face urgent collateral or cash needs due to margin calls.
- Insurance and pension sectors increased integration with asset management, raising exposure to leverage, liquidity mismatches, and valuation uncertainty (examples include LDI stresses in UK pension funds in 2022).

### Systemic Liquidity Stress and Interconnectedness
- Systemic liquidity events arise when numerous institutions experience liquidity strains simultaneously; market valuation shocks can trigger and propagate such stress via interconnections.
- Amplification channels include:
  - Leverage (including off-balance-sheet contracts)
  - Counterparty credit risk (defaults on contracts often stemming from liquidity distress)
  - Funding risk (loss of access to funding from distressed counterparties)
- Examples and metrics:
  - Margin calls can rapidly drain liquidity; the collapse of Archegos in 2021 inflicted more than $10bn in losses on banks via leveraged, concentrated, opaque investments.
  - In early 2025, trade tensions caused large swings across equity, bond, and commodity markets, generating significant margin calls.
- Cross-exposures are widespread, especially in advanced economies; in the US and Europe some large banks have NBFI exposures exceeding their Tier 1 capital.
- Flow-of-funds statistics capture balance-sheet linkages, but off-balance-sheet exposures (derivatives, repos) can further increase interconnectedness.
- Cross-border portfolio investments channel global liquidity cycles into EMDEs; shocks can first hit equity and bond markets, then ripple into the domestic financial system via local dash-for-cash behavior and exchange-rate effects.
- FX liquidity risk: large capital outflows raise demand for hard-currency FX liquidity and can lead to bank FX shortages or sharp currency depreciation. Central banks’ FX backstop capacity is limited by international reserves.

### Need for a Systemwide Perspective
- Definition: systemwide analysis—an interconnectedness exercise considering multiple key sectors, capturing direct (cross-exposures) and indirect (common exposures, firesale price dynamics, margin calls) contagion effects.
- IMF use: systemwide liquidity analysis has been applied in FSAPs and technical assistance for nearly a decade; these bilateral exercises often rely on confidential country-specific data, covering broad sectors including nonfinancial sectors when relevant.
- Complementary to: global vulnerability assessments, standard-setting, national exercises, and recommendations by FSB, ESRB, and national authorities (e.g., BoE SWES).

### Literature and Theory (high-level)
- Foundational and post-GFC work covers idiosyncratic and systemic runs (Diamond and Dybvig; Allen and Gale; Morris and Shin; Holmstrom and Tirole; Freixas, Parigi, and Rochet; Rochet and Vives).
- Post-GFC amplification mechanisms highlighted include:
  - “Run on repos,” collateral channels, fire sales, interplay of market and funding liquidity, leverage cycles, and cash hoarding/network effects.
- Recent advances emphasize margin and collateral call dynamics, central clearing complexities, and CCPs as liquidity transformers; margin procyclicality can exacerbate interbank hoarding and fragility.

### Empirical and Operational Risk Assessment
- Data landscape:
  - Regulators collect granular confidential data for banks and insurers.
  - Security-level holdings, NAVs, and flows are publicly available for many investment funds.
  - Sparse supervisory/public data for hedge funds and private family offices (“dark corner”).
  - FMI transaction-level data exist but are resource-intensive to process.
- Quantitative approaches:
  - Banking contagion models exploit supervisory interbank matrices and network methods (Eisenberg–Noe lineage).
  - Investment fund stress tests generally follow a three-step structure: (1) market shocks reduce NAVs, (2) redemptions rise, (3) asset sales create price impacts driving further NAV reductions (second-round effects).
  - CCP stress tests focus on member default and CCP resilience but often do not assess systemwide resilience including members’ clients or leveraged positions.
- Regulatory data gaps across NBFI segments (as summarized):
  - Investment funds (excluding MMFs and hedge funds): $58 trillion, 12% of GFA — notable data limitations in some vulnerability areas.
  - Insurance: $40 trillion, 9% of GFA.
  - Pension funds: $43 trillion, 9% of GFA.
  - Money market funds: $8.5 trillion, 2% of GFA.
  - Structured finance vehicles: $6 trillion, 1% of GFA.
  - Hedge funds: $6 trillion, 1% of GFA.
  - Central counterparties: $0.7 trillion, 0.1% of GFA.
  - (GFA = global financial assets)

### IMF’s Systemwide Analysis Tools
- Two standardized tools:
  - Excel-based systemwide liquidity analysis tool (Balance Sheet Approach / BSA using sector-aggregate flow-of-funds by counterpart).
  - Market Impact from Investment Funds Liquidity Distress (MILD) — an investment fund liquidity stress-testing dashboard.
- Purpose: parsimonious, top-down tools that identify amplification channels, systemic sectors, market spillovers, and data gaps; support sectoral stress test interpretation and policy discussions.

### Excel-Based Systemwide Liquidity Analysis Tool (summary)
- Uses sector-aggregate flow-of-funds data detailing financial assets/liabilities by sector, counterparty, and instrument.
- Runs cash-flow-based liquidity stress tests across systemically important sectors while ensuring cross-sectoral consistency.
- Captures how liquidity stress shifts across sectors (e.g., investment fund redemptions withdrawing bank deposits transfer stress to banks).
- Highlights importance of reinvestment destination (domestic banks vs assets outside domestic system like gold or foreign stablecoins).
- Particularly effective for linking financial stability with external vulnerability in EMDEs and small open economies; emphasizes central bank international reserves when FX liquidity stress is driven by capital flows.
- Results sensitive to behavioral assumptions and liquidation order—multiple scenario and sensitivity analyses recommended.

### MILD (Market Impact from Investment Funds Liquidity Distress)
- Modular, scenario-based stress-testing framework built on granular fund- and asset-level data.
- Core components:
  - Redemption shocks calibrated using parametric assumptions, historical flows, or flow-performance relationships.
  - Optional market shocks to asset valuations.
  - Modeling of asset liquidity, liquidation pecking orders, and mitigating actions (e.g., short-term repo borrowing).
- Mechanism: translate funds’ liquidity demand into asset sales under different behavioral assumptions (waterfall, pro-rata, mixed), then apply market impact functions to map sales volumes into price declines by asset segment.
- Outputs: liquidity shortfalls, assets sold, market price impact, and losses to funds and other sectors presented as distributions across scenarios.
- Limitations:
  - Partial-equilibrium framework—not full systemwide consistency or general-equilibrium dynamics.
  - Does not track reinvestment of redeemed funds.
  - Sensitive to behavioral assumptions, liquidation strategies, and market depth parameters.
  - Intended as scenario-based indicators of vulnerability and amplification, not point forecasts.

### FSAP Applications: Common Approach and Country-Specific Adaptations
- Common methodology: top-down, scenario-based approaches tailored to jurisdiction-specific vulnerabilities and data availability; estimate liquidity needs and trace direct/indirect spillovers under alternative behavioral assumptions.
- Early and notable country applications:
  - Luxembourg (2017), Andorra, Mauritius, Sweden (Article IVs): reserve adequacy and enhancing central bank LOLR role.
  - Armenia (2018): recommended FX-focused reserve requirement adjustments to address dollarization and FX liquidity mismatches.
- Illustrative country groups and key issues:
  - Low-income country: main risks from public finance stress, FX deposit runs, and foreign investor exits; recommendation to allow banks to satisfy FX-dedicated reserve requirements in hard currency and hold global safe assets if FX LCR is introduced.
  - Emerging market: capital outflow shocks transmit across sectors; NFCs can be highly vulnerable; central bank may adjust FX reserve requirement ratio to increase usable FX buffers.
  - High-income commodity exporter: central bank reserve backing constraints under fixed exchange rate regimes; recommendation to introduce contingent flexibility in reserve backing and consider FX LCR and preemptive prudential measures.
- Selected FSAP country examples (tool enhancements and findings):
  - Philippines (2021): linked banks and NFCs under loan moratoria; NFCs can be systemically important due to liquidity positions outside prudential perimeter.
  - Chile (2021): institution-level analysis of banks, mutual funds, and pension funds; recommended improving pension fund regulation, mutual fund liquidity management, bank liquidity stress tests, interbank repo development, and central bank collateral/ELA framework.
  - Türkiye (2023): FX liquidity risks with high inflation (~80 percent in mid-2022) and deposit dollarization; central bank–bank nexus showed FX assets held at central bank about double readily available FX gross international reserves in mid-2022; tests indicated banks withstand moderate FX stress but severe outflows could drain reserves.
  - Iceland (2023): small open economy vulnerabilities to foreign investor withdrawals; central bank had sufficient reserves partly due to boosting gross international reserves with external borrowing (more than 40 percent of gross international reserves funded by external borrowing).
  - India (2024): NBFCs’ reliance on wholesale funding and bond funds; CDMDF (Corporate Debt Market Development Fund) provides liquidity backstop but not sufficient for all pressures; India’s relatively closed capital account means stress redistributes liquidity rather than producing aggregate FX shortages.
  - Mexico (2022): enhanced tool to assess capital outflows from local sovereign bond market, using granular BSA data including institution-level exposures to sovereign bonds, repos, derivatives, and liquid asset buffers; stress scenarios showed banks’ central role in system liquidity backstopping and development banks’ vulnerabilities under market behavioral constraints.
  - Euro Area: advanced systemwide analysis incorporated margin calls from derivatives and collateral calls from repos, transaction-level supervisory data, and modeled immediate (two-day) vs short-term (two-week) dynamics given T+2 settlement; highlighted MMFs’ pivotal amplifying role and that second-round effects materially magnify initial shocks.
  - United States (2020 FSAP): sectoral stress tests across banks, insurers, mutual funds, MMFs, and NFCs connected to assess contagion from NFC debt distress; mutual fund asset liquidations could significantly price-impact EM and high-yield bonds; results sensitive to market behaviors and price-impact estimation.

### Key Takeaways from FSAP Experience
- Systemwide liquidity analysis must be tailored to each jurisdiction’s financial structure, vulnerabilities, and data availability.
- Common patterns:
  - In less complex, externally exposed economies, Excel-based BSA is useful to trace capital outflows, FX pressure, and nonfinancial sector propagation.
  - In advanced market-based systems, focus is on bank–NBFI linkages, common exposures, fire-sale dynamics, and repo/derivatives margin and collateral calls.
- Limitations and sensitivities:
  - Results highly sensitive to behavioral assumptions, fire-sale price-dynamics calibration, perimeter of covered institutions/instruments, and scenarios considered.
  - Most exercises avoid declaring pass/fail thresholds; instead they identify transmission channels, systemic actors, data gaps, safety nets, and analytical priorities.
  - “Soft” recommendations predominate (methodological advances, stronger supervision, data gaps closure), because regulatory fixes (e.g., increasing fund liquid assets) can create new spillovers.
- International consensus on managing systemwide liquidity risks and appropriate central bank backstop roles remains unsettled.

### Way Forward: Data, Behavior, and Methodological Challenges
- Data gaps are the primary constraint:
  - Need cross-sectoral interconnectedness data among banks, NBFIs, and relevant nonfinancial/public sectors.
  - Missing: off-balance-sheet items (derivatives, repos, credit lines), cross-border transactions concentrated in tax havens, and activity-level FMI data that are resource-intensive to process.
- Near-term approaches to fill data gaps:
  - Use confidential counterparty data from regulated entities (especially banks) to map significant NBFI activities and concentrated exposures.
  - Leverage FMI transaction-level data to monitor margin and collateral calls under stress.
  - Greater collaboration with national authorities required due to confidentiality and data-processing burdens.
- Behavioral uncertainty:
  - Agents’ responses are complex, time-varying, and psychology-driven in stress episodes; systemwide exercises therefore explore a range of behavioral assumptions and rely on expert judgment.
  - Bottom-up exercises (e.g., BoE SWES) help reveal realistic behavioral patterns that inform advanced models, including agent-based models (ABMs).
- Market microstructure and clearing arrangements matter:
  - Margin formulas, settlement cycles (T+2), CCP opacity, and bilateral vs centrally cleared trades materially affect stress propagation.
  - CCP stress testing should evolve to incorporate systemwide perspectives given that stress can originate from members or clients even when CCPs appear resilient.
- Consistency in agent actions is crucial in systemwide analysis:
  - Reinvestment behavior matters (redeemed funds reinvested domestically vs moved outside the system).
  - Standard sectoral stress-test assumptions may be unrealistic in a systemwide setting (e.g., simultaneous household withdrawals from banks and funds without reinvestment).
  - Precautionary liquidity hoarding by otherwise resilient banks can amplify contagion by constraining funding to other agents.
- Technical estimation challenges:
  - Estimating sale-price dynamics in illiquid markets is difficult; volatility-based price-impact methods can yield counterintuitive results in low-trade markets.
  - Equilibrium approaches matching supply and demand may be more reliable where trading is sparse.
- Overall: continue combining top-down tools (Excel-based BSA, MILD), bottom-up exercises, FMI data use, and behavioral insights to improve systemwide liquidity stress testing while expanding data collection and inter-agency collaboration.

*Source: IMF staff—Introduction, wpiea2026170-source-pdf*

### Conclusion

### Conclusion

### Progress in systemwide risk analysis
- The IMF has made significant progress in developing top-down systemwide risk analysis over the past decade.
- This approach is crucial for assessing systemic risks from NBFIs and their spillover effects to banks, other NBFIs, and across borders given their systemwide interconnectedness.
- Methodological advances have been published and applied in FSAPs.
- Early applications for less complex EMDEs helped to identify areas for improvement and demonstrated how stress test results can inform policy recommendations on systemic liquidity.
- Recent work has focused more on NBFIs, market finance, and new liquidity risks from margin and collateral calls for more complex systems, aligning with FSB’s current initiatives (FSB, 2024b).
- Enhanced access to transaction-level data, enabled by post-GFC reforms of financial market infrastructures like CCPs and data repositories, has supported this progress.

### Data, methods, and emerging priorities
- Evaluations will increasingly depend on transaction-level data collected by FMIs, supplemented where possible by partial entity or counterparty data reported by regulated institutions.
- Bottom-up exercises are another valuable approach.
- All these methods demand significant resources and underscore the importance of close, ongoing collaboration with national authorities, potentially requiring a multi-year engagement that extends beyond the FSAP timeline.
- Further progress is needed to strengthen analytical capabilities for assessing near-term financial stability risks related to NBFIs and their interconnectedness.

### Specific analytical gaps and examples
- A deeper understanding of the risks associated with the increasing prevalence of hedge fund basis trades—financed through repo transactions amid rising public debt in core markets—is essential in some core markets (see BIS Quarterly Bulletin, December 2025, and the October 2024 GFSR).
- Such evaluations will increasingly depend on transaction-level data collected by FMIs, supplemented where possible by partial entity or counterparty data reported by regulated institutions.

### Uses, limitations, and policy-relevant outputs
- Given the challenges, systemwide risk analysis is usually not suited to draw strong conclusions about the resilience of the system upon shocks.
- Nevertheless, these exercises are useful in identifying:
  - potential weak links;
  - critical data gaps;
  - priorities for strengthening or streamlining supervisory and reporting frameworks;
  - areas for improving data sharing and cross-agency coordination;
  - regulatory features that could be adjusted to better support system-wide stability.
- Systemwide analysis can also help identify industry rules and practices that could help one sector’s resilience but possibly at the cost of the system, such as margin practices.

*Source: wpiea2026170-source-pdf — Conclusion*

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_Source: https://www.imf.org/-/media/files/publications/wp/2026/english/wpiea2026170-source-pdf.pdf_