## wp17153 - 1. Key Data used for FSA

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### I. Introduction and paper objectives
- Context and motivation:
  - Charles Kindleberger’s 1978 work “Manias, Panics and Crashes” referenced for historical perspective on financial crises.
  - Global financial crisis (GFC) of 2007/8 highlighted data shortcomings that hampered monitoring in advance of the crisis.
  - Major statistical manuals (SNA and BPM) are updated around every 16 years; SNA and BPM were last updated in 2008 and 2009, respectively.
- Measured impact cited:
  - Laeven and Valencia (2003) estimated median output losses of banking crises between 1970 and 2011 at 23.2 percent of GDP.
  - Updated work found that for crises that started in 2007 onwards, the median output loss reached 25 percent for those countries that experienced a banking crisis.
- Main aims:
  - Take a holistic view of data actually used for FSA and draw out common international threads.
  - Set out data gaps identified by policy makers—particularly shadow banking, capital flows, corporate borrowing, demand for more granular data, remaining maturity and foreign currency data—and propose how macroeconomic statistical manuals can better meet FSA needs.
- Scope and limits:
  - Focuses on user needs and how they could be addressed; does not specifically address implementation challenges, costs, and trade-offs.
  - Recognizes user needs and priorities differ by country circumstances.
- Recent initiatives:
  - References G-20 Data Gaps Initiative (DGI) and other statistical responses to data needs.

### II. Definition and remit of financial stability and FSA
- Definitions and remit:
  - BIS/FSB/IMF August 2016 report: macro-prudential policy aims at avoiding “the risk of widespread disruption to the provision of financial services that is caused by an impairment of all or parts of the financial system, and which can cause serious negative consequences for the real economy.”
  - Financial stability encompasses prudential supervision, market conduct regulation, consumer protection, land supply, tax system, exchange rate regime, market infrastructure, corporate governance, and investor protection.
  - Bank of Korea definition: financial stability is “a condition in which the financial system works smoothly with all of its key components satisfactorily performing their roles: financial institutions carrying out their financial intermediary functions, market participants maintaining a high level of confidence in their financial market, and the financial infrastructure being well developed.”
- Purpose beyond crisis avoidance:
  - Concerned with continuity and efficiency of financial services and identifying policies to improve efficiency and reduce systemic risk.

### III. Relationship among micro-prudential, macro-prudential, macroeconomic policy, and FSA
- Complementarity and interaction:
  - Micro-prudential supervision predates the GFC; macro-prudential policy emerged because micro-prudential alone was insufficient.
  - Macro-prudential analysis: “looks at the intersection of the real economy and the financial sector, providing a bird’s eye view of the entire system instead of focusing on individual instruments and individual institutions.”
  - Macroeconomic developments and policy are directly relevant to financial stability risks and vice versa.
- Data implications:
  - Micro-prudential analysts need macro data; macro-prudential analysts need granular micro data.
  - Breaking silos between macro-economists and financial sector specialists is encouraged.
  - IMF’s Financial Surveillance Strategy (August 2012) emphasizes understanding interactions across policy domains and potential costs and side effects.

### IV. Governance arrangements and institutional developments for FSA
- Institutional evolution since the GFC:
  - Allocation of financial stability responsibility within domestic economies (often to central banks); creation of the Financial Stability Board (FSB); enhanced national and international regulation of banks.
  - Growth in financial stability departments and establishment of financial stability committees; BIS’s Financial Stability Institute assists supervisors.
- Reporting and surveillance:
  - National financial stability reports typically published semi-annual; IMF produces a semi-annual Global Financial Stability Report (GFSR).
  - Meaningful data are essential to these reports.
- FSAP (Financial Sector Assessment Program):
  - Goal: gauge stability and soundness of the financial sector and assess its contribution to growth and development.
  - Three components: soundness of banks and other financial institutions (including stress tests); quality of financial market oversight; ability of supervisors, policy makers, and safety nets to respond in a crisis.
  - Data requirements focus on the first component; second and third are qualitative and include Financial Soundness Indicators (FSIs).
  - Economies with systemically important financial sectors are required to have mandatory FSAPs every five years.
  - Identification of such economies uses GDP on a purchasing power parity basis, BIS Locational International Banking Statistics (IBS), and IMF Coordinated Portfolio Investment Survey (CPIS).
  - Presently 29 economies are classified as having systemically important financial sectors.

### V. Key data themes and gaps highlighted
- Principal user-identified gaps:
  - Shadow banking.
  - Capital flows (timeliness, frequency, geographic/currency breakdowns).
  - Corporate borrowing (foreign currency, offshore affiliates).
  - Demand for more granular data and micro-data sharing.
  - Remaining maturity and foreign currency data.
- Statistical response and priorities:
  - Statistical world reacted with initiatives including the G-20 DGI; remaining questions on additional actions and prioritization.
  - Statisticians need to discuss priorities with users before embarking on enhancements; trade-offs differ across countries.

### Stress testing: approaches, uses, and data needs
- Approaches and formats:
  - Balance sheet approach: draws on balance sheet data of deposit-takers and other financial institutions.
  - Market price-based approach: uses market data and statistical techniques to capture interlinkages.
  - Top-down: national authorities or IMF staff using bank-by-bank data and consistent methodology.
  - Bottom-up: individual financial institutions using internal data and models based on a common scenario.
- Data implications:
  - Stress tests are data intensive and require granular, well maintained, consistent databases with appropriate access.
  - Few stress-testing models correctly measure the resilience of the financial system as a whole and its ability to continue providing financial intermediation in a way readily actionable for banks and supervisors.

### Financial stability policy: tools and scope (from BIS/FSB/IMF August 2016 report)
- Policy toolkit examples:
  - Broad-based capital tools: dynamic provisioning, countercyclical capital buffers, time-varying leverage ratio caps.
  - Sectoral capital and asset-side tools: limits on foreign currency loans to corporates, caps on loan-to-value (LTV), debt-service-to-income (DSTI), or loan-to-income (LTI) ratios.
  - Liquidity-related tools: liquidity coverage ratio (potentially calibrated by currency), core funding ratios, levies on volatile funding, caps on loan-to-deposit ratio.
  - Capital surcharges for G-SIBs and D-SIBs; scheduled from 2022 for global systemically important insurers (G-SIIs).
  - Interbank exposure limits, foreign and domestic currency reserve requirements, central clearing of OTC derivatives, margining requirements and liquidity resources for CCPs.
- Broader policy interactions:
  - Tax incentives for debt finance, land and housing policies, consumer protection, monetary policy, exchange rate movements, and capital flow measures can affect financial stability.
- Data sharing and transparency:
  - IMF, in consultation with FSB and BIS, compiling a publicly available macro-prudential policy database welcomed by the G-20 in March 2017 Communique.

### Core purposes of datasets used for FSA
- Monitoring soundness and efficiency of the financial system and growth of credit and indebtedness of non-financial sectors.
- Identifying pockets of vulnerability within the financial system.
- Assessing sustainability and vulnerability of non-financial sector debt positions, impact of asset price growth, and financial links that may propagate shocks.
- Testing potential vulnerabilities through stress tests.
- Common themes from FSAPs and financial stability reports: structure of financial sector, relevance of credit and debt statistics, need to monitor asset prices, and importance of both time-series and cross-sectional/position data.

### Cross-sectional vs time-series dimension; residence-based vs cross-border consolidated data
- Two dimensions of systemic risk:
  - Time dimension: build-up of risks over time.
  - Cross-sectional dimension: interconnectedness and distribution of risk at a point in time.
- Data views:
  - Majority of domestic policymakers use residence-based data to protect residents and the domestic economy (credit, debt, markets, market infrastructure, inclusion, domestic interconnectedness).
  - Cross-border consolidated data used for risks from domestically-owned institutions’ activities abroad; deposit-taker data typically analyzed on a cross-border consolidated basis for micro- and macro-prudential purposes.
  - BIS IBS consolidated data provide nationality-based exposures and country risks; locational IBS enhancements add nationality-of-reporting-bank detail.
  - Both residence-based and consolidated views are important (e.g., interest in offshore borrowing and U.S. dollar borrowing by foreign subsidiaries of emerging market NFCs).

### Data limitations and attributes of useful financial data
- Financial data must have three attributes: (1) sufficient scope (comprehensive and granular), (2) high quality (comprehensive, accurate, timely), and (3) accessible (shared and secured).
- Identification of data gaps begins with priority questions, analytical framework, and data needed to quantify them.
- The degree of market sophistication and interconnectedness affects the scope of data monitored for FSA.

### Appendix highlights — Specific data gaps and suggested ways forward

- Shadow banking
  - Findings:
    - Shadow banking performs credit and maturity transformation, can be systemically important, often less regulated, lacks access to deposit insurance and central bank facilities.
    - Data on securities financing activities (repo, securities lending) are lacking; sectoral balance sheets and flow of funds have limitations by economic function, maturity, liquidity, and currency.
  - Way forward:
    - Share experiences among statisticians, regulators, and users; frequent dissemination; support FSB efforts and IAG Working Group work; FSB to develop regular flow of securities financing market data at national and global levels by end-2018.

- Capital flows
  - Findings:
    - BoP is key but needs more timely data, higher frequency indicators, direction of flows between countries, separation of NFC flows from financial sector, geographic and currency breakdowns, remaining maturity, and off-balance sheet items.
    - DGI-2 moves include CPIS sector breakdowns and quarterly reporting by 2019.
  - Way forward:
    - IMF BOPCOM to undertake a holistic review of cross-border exposures data; aggregate G-SIBs common data template for early indications of cross-border flows.

- Corporate borrowing
  - Findings:
    - BIS database: NFC debt in major EMEs increased from less than 60 percent of GDP in 2006 to 110 percent at end-2015.
    - Gaps: foreign currency borrowing through offshore affiliates; corporates’ risk exposures (leverage, maturity, FX exposures, hedging).
    - Offshore borrowing shares via international debt securities by nationality NFCs as of September 2015: Chinese 93 percent, Brazilian 53 percent, Russian 45 percent.
  - Way forward:
    - DGI-2 Recommendation 14: improve consistency and dissemination of NFC cross-border exposure data; short-term combine residence-based BoP with BIS IBS and IDS; consider enhanced hedge disclosures.

- Granular and micro-data
  - Findings:
    - Increased need for detailed, granular information across sector, country, and currency dimensions; micro-data face confidentiality constraints.
    - Initiatives: G-SIBs common data template, repo and securities financing transaction data, enhanced BIS IBS, sectoral balance sheets, enhanced IMF CPIS.
  - Way forward:
    - Continue DGI-2 Recommendation 20 to promote data sharing within jurisdictions and with other national authorities; international organizations facilitate experience exchange and trust-building.

- Real estate markets
  - Findings:
    - Monitoring residential and commercial real estate critical; DGI and BIS RPPI coverage expanded; CPPI coverage expanding since 2016 but limited.
    - Need complementary indicators: price-to-rent, price-to-income ratios.
  - Way forward:
    - International guidance on RPPI exists; CPPI guidance in early stages; ISWGPS developing housing-related indicators under DGI-2 Recommendation 17.

- Insurance companies
  - Findings:
    - Insurance sector can be systemic; IAIS identified G-SIIs with scheduled capital surcharges from 2022.
    - Gaps: liability structures, duration gaps, common exposures, interconnections, cross-border links.
  - Way forward:
    - DGI-2 Recommendation 4: consider a common data template for G-SIIs and potential long-term granular collection.

- Households
  - Findings:
    - Need comprehensive household data: assets/liabilities composition, household income, debt service payments, distributional information.
    - Household surveys are key but costly; administrative data could complement surveys subject to confidentiality.
  - Way forward:
    - Share national experiences on household data compilation; DGI-2 Recommendations 8 and 9 encourage production and dissemination of distributional information based on sectoral accounts.

- Summary table (selected highlights)
  - Shadow Banking: gaps in heterogeneous institutions, inconsistent definitions, insufficient economic-function data; way forward: FSB monitoring, IAG sector account work, experience sharing.
  - Capital Flows: gaps in timeliness, frequency, direction, NFC separation, geographic/currency, maturity/exposure details; way forward: IMF BOPCOM review, G-SIBs template aggregation.
  - Corporate Borrowing: gaps in offshore foreign currency borrowing and hedging details; way forward: combine BoP with BIS IBS/IDS; improved hedge disclosures.
  - Granular Data: confidentiality constraints and data quality/consistency issues; way forward: promote data sharing platforms and IO facilitation.
  - Real Estate / Insurance / Households: data coverage/quality gaps and proposed national/DGI-2 actions.

### How can FSA data needs be addressed in macroeconomic statistical manuals?
- Rationale:
  - Review SNA, BPM, MFSMCG, External/Public Debt guides to reflect increased policy focus on financial stability and support integrated datasets.
- Suggested enhancements consistent with SNA framework:
  A. Nonperforming loans (NPL) and provisions
    - Options:
      - Introduce NPLs at nominal value into central framework for all sectors, with flows as other changes in volume of assets (OCVA).
      - Bring provisions for losses on nominal-valued assets into central framework (preferred); record flows as OCVA to reflect profitability and capital effects.
  B. Notional value of derivatives
    - Proposal: add notional values of financial derivative positions (by risk category and sector) as memorandum items for an economy-wide residence-based picture.
  C. Remaining maturity
    - Proposal: bring remaining maturity into central framework; consider finer within-up-to-one-year breakdown at three months.
  D. Foreign currency
    - Proposal: introduce foreign currency/domestic currency breakdown into central frameworks of SNA and BPM, combined with remaining maturity breakdowns; consider memorandum splits by major currency.
  E. Sub-sector breakdown of NBFI
    - Proposal: review the 2008 SNA seven NBFI sub-sectors informed by FSB economic-function analysis (five functions).
  F. Distinctions based on size
    - Proposal: investigate compiling/disseminating size-based data (household income level, NFC size, deposit-taker size) as memorandum items leveraging DGI household distributional work.

### Concluding remarks
- Since the GFC, FSA governance and macro-prudential analysis have grown; common patterns of data use emerge across countries despite differences.
- Continued work required on shadow banking, capital flows, corporate borrowing, and granular data.
- Implementing selected enhancements to macroeconomic manuals (provisions, remaining maturity, foreign currency breakdowns) can support FSA while preserving conceptual frameworks.

*Source: IMF Working Paper wp17153 — 1. Key Data used for FSA (excerpt).*

### 1. Key Data used for FSA ...............................................................................................

### wp17153 - 1. Key Data used for FSA

### I. Introduction and paper objectives
- Context:
  - Charles Kindleberger’s 1978 work “Manias, Panics and Crashes” referenced for historical perspective on financial crises.
  - Recent decades, notably the global financial crisis (GFC) of 2007/8, increased focus on financial stability analysis (FSA).
  - The GFC highlighted data shortcomings that hampered monitoring in advance of the crisis.
- Measured impact cited:
  - Laeven and Valencia (2003) estimated median output losses of banking crises between 1970 and 2011 at 23.2 percent of GDP.
  - Updated work found that for crises that started in 2007 onwards, the median output loss reached 25 percent for those countries that experienced a banking crisis.
- Main aims of the paper:
  - Take a holistic view of data actually used for FSA, drawing out common international threads in analysis.
  - Set out data gaps identified by policy makers—particularly regarding shadow banking, capital flows, corporate borrowing, demand for more granular data, remaining maturity and foreign currency data—and propose how macroeconomic statistical manuals can better meet FSA needs.
- Scope and limits:
  - The paper focuses on user needs and how they could be addressed; it does not specifically address implementation challenges, costs, and trade-offs.
  - Recognizes that user needs and priorities will differ by country circumstances.
- Timing and background on statistical manuals:
  - Major statistical manuals (SNA and BPM) are updated around every 16 years; SNA and BPM were last updated in 2008 and 2009, respectively.
- Recent international initiatives referenced:
  - G-20 Data Gaps Initiative (DGI) and other statistical responses to data needs.

### II. Definition and remit of financial stability and FSA
- Definitions and interpretations:
  - BIS/FSB/IMF August 2016 report: macro-prudential policy aims at avoiding “the risk of widespread disruption to the provision of financial services that is caused by an impairment of all or parts of the financial system, and which can cause serious negative consequences for the real economy.”
  - Financial stability has broader remit than macro-prudential policy, including prudential supervision, market conduct regulation, consumer protection, land supply, tax system, exchange rate regime, market infrastructure, corporate governance, and investor protection.
  - Bank of Korea: financial stability is “a condition in which the financial system works smoothly with all of its key components satisfactorily performing their roles: financial institutions carrying out their financial intermediary functions, market participants maintaining a high level of confidence in their financial market, and the financial infrastructure being well developed.”
  - No universally accepted definition, but broad consensus that financial stability refers to the smooth functioning of the key elements of the financial system.
- Purpose beyond crisis avoidance:
  - Financial stability policy concerned with continuity and efficiency of financial services and with identifying where policy can improve efficiency and reduce systemic risk.

### III. Relationship among micro-prudential, macro-prudential, macroeconomic policy, and FSA
- Complementarity and interaction:
  - Micro-prudential supervision existed before the GFC; the crisis showed it was necessary but not sufficient—giving rise to macro-prudential policy.
  - Macro-prudential analysis provides a system-wide perspective: “macro-prudential analysis looks at the intersection of the real economy and the financial sector, providing a bird’s eye view of the entire system instead of focusing on individual instruments and individual institutions.”
  - Macroeconomic developments and policy are directly relevant to financial stability risks and vice versa (e.g., rapid growth can encourage excessive credit growth; weak economic position can increase nonperforming loans).
  - Traditional macroeconomic indicators remain relevant for FSA, but macro-prudential policy focuses on strengthening financial system defenses rather than managing aggregate demand or the business cycle.
- Data implications:
  - Micro-prudential analysts need macro data; macro-prudential analysts need granular micro data.
  - Breaking silos between macro-economists and financial sector specialists is encouraged.
  - The IMF’s Financial Surveillance Strategy (August 2012) emphasizes understanding interactions between macro-prudential, macroeconomic, and micro-prudential policies and potential costs and side effects.

### IV. Governance arrangements and institutional developments for FSA
- Institutional evolution:
  - Enhanced domestic and international institutional arrangements since the GFC, including:
    - Allocation of financial stability responsibility within domestic economies (often to the central bank).
    - Creation of the Financial Stability Board (FSB) and the convening of G-20 leaders.
    - Enhanced regulation of banks nationally and internationally.
  - Central banks have increased focus on financial stability and many countries have established financial stability committees.
- Reporting and surveillance:
  - Financial stability reports published regularly (usually semi-annual) at national level to inform the public on risks.
  - IMF produces a semi-annual Global Financial Stability Report (GFSR).
  - Meaningful data are essential to these reports at national and international levels.
- Strengthening of capacity:
  - Growth in financial stability departments domestically and internationally.
  - The FSB coordinates national authorities and standard-setting bodies to promote implementation of effective regulatory, supervisory, and other financial sector policies.
  - BIS’s Financial Stability Institute assists supervisors around the world.
- FSAP (Box 1) — Financial Sector Assessment Program:
  - Goal: gauge stability and soundness of financial sector and assess its potential contribution to growth and development.
  - Three key components examined:
    - the soundness of banks and other financial institutions, including stress tests;
    - the quality of financial market oversight in banking and, if appropriate, insurance and securities;
    - the ability of supervisors, policy makers, and financial safety nets to respond effectively in case of a crisis.
  - Data requirements focus on the first component; the second and third are qualitative and include Financial Soundness Indicators (FSIs).
  - Economies identified as having systemically important financial sectors are required to have mandatory FSAPs every five years.
  - Identification of such economies is based on GDP data on a purchasing power parity basis, BIS Locational International Banking Statistics (IBS), and IMF Coordinated Portfolio Investment Survey (CPIS).
  - Presently 29 economies are classified as having systemically important financial sectors.

### V. Key data themes and gaps highlighted
- User-identified data gaps and demands:
  - Shadow banking.
  - Capital flows.
  - Corporate borrowing.
  - Demand for more granular data.
  - Need for remaining maturity and foreign currency data.
- Statistical response and initiatives:
  - Statistical world has reacted with initiatives including the G-20 Data Gaps Initiative (DGI), but questions remain about what more needs to be done.
- Prioritization and implementation:
  - Statisticians need to address challenges, costs, and trade-offs and discuss priorities with users before embarking on data enhancements.
  - Users’ needs and priorities will differ across countries; the paper focuses on identifying needs and exploring approaches.

*Source: wp17153 - 1. Key Data used for FSA (IMF working paper excerpt).*

### 2014. See www.imf.org/external/pubs/ft/survey/so/2014/POL011314A.htm

### wp17153 - 2014

### Stress testing: approaches, uses, and data needs
- Stress tests have become integral to financial stability analysis (FSA), using extreme but plausible stress scenarios to test resilience and the ability of the financial system to continue to provide financial services.
- Two common methodological approaches:
  - The balance sheet approach: draws on balance sheet data of deposit-takers and other financial institutions. (See “Introduction to the Balance Sheet-Based Approach to Stress Testing,” Schneider and Schumacher.)
  - The market price-based approach: uses market data and statistical techniques to capture interlinkages between institutions, markets, or sources of risk.
- Implementation formats:
  - Top-down: conducted by national authorities or IMF staff (typically in FSAPs) using bank-by-bank data and a consistent methodology and assumptions.
  - Bottom-up: conducted by individual financial institutions using their internal data and models based on a common scenario.
- Data implications:
  - Stress tests are data intensive and require granular, well maintained, consistent databases with appropriate access.
  - Few stress-testing models correctly measure the resilience of the financial system as a whole and its ability to continue providing financial intermediation in a way that is readily actionable for banks and supervisors. (Demekas, IMF Working Paper 15/146.)

### Financial stability policy: tools and scope
- Policy toolkit (as discussed in the August 2016 BIS/FSB/IMF G-20 report) includes:
  - Broad-based capital tools: dynamic provisioning, countercyclical capital buffers, time-varying leverage ratio caps.
  - Sectoral capital and asset-side tools: limits on foreign currency loans to corporates, caps on loan-to-value (LTV), debt-service-to-income (DSTI), or loan-to-income (LTI) ratios.
  - Liquidity-related tools: liquidity coverage ratio (potentially calibrated by currency), tools to contain maturity mismatch (core funding ratios), price-based tools (levy on volatile funding), caps on loan-to-deposit ratio.
- Other tools and policies:
  - Capital surcharges for G-SIBs and D-SIBs, and scheduled from 2022, for global systemically important insurers (G-SIIs); increases in risk-weights and large exposure/concentration limits.
  - Interbank exposure limits, and foreign and domestic currency reserve requirements.
  - Policies addressing non-bank activities: central clearing of OTC derivatives, resilience of central counterparties (margining requirements and liquidity resources).
- Broader policy interactions:
  - Tax system incentives for debt finance, land and housing policies, and consumer protection affect financial stability.
  - Debate exists on whether monetary policy (interest rates) should be used to meet financial stability objectives; monetary policy and financial stability objectives are interrelated.
  - Exchange rate movements can have domestic financial stability implications.
  - Capital flow measures can overlap with macro-prudential policies when aimed at limiting systemic risks by influencing capital flows.
- Data sharing and transparency:
  - IMF, in consultation with the FSB and the BIS, is compiling a publicly available macro-prudential policy database. The development of this database was welcomed by the G-20 Finance Ministers and Central Bank Governors in their March 2017 Communique.

### Data used in Financial Stability Analysis (FSA): main story lines
- Core purposes of datasets used for FSA:
  - Monitoring soundness and efficiency of the financial system and the growth of credit and indebtedness of non-financial sectors.
  - Identifying pockets of vulnerability within the financial system.
  - Assessing sustainability and vulnerability of non-financial sector debt positions, the impact of asset price growth, and financial links that may propagate shocks.
  - Testing potential vulnerabilities through stress tests.
- Common data themes emerging from a review of FSAPs and financial stability reports:
  - Structure of the financial sector, relevance of credit and debt statistics, the need to monitor asset prices.
  - Emphasis on both time-series analysis and cross-sectional/position data to capture systemic risk’s time and cross-sectional dimensions.
- Sample and review evidence:
  - Authors reviewed 23 recent IMF FSAPs (list includes Algeria, Argentina, Barbados, Belarus, Canada, Comoros, Republic of Congo, Denmark, El Salvador, Germany, Hong Kong SAR, Ireland, Montenegro, Morocco, Peru, Republic of Korea, Russia, Samoa, South Africa, Switzerland, Tajikistan, United Kingdom, and United States) and financial stability reports of Australia, People’s Republic of China, ECB, IMF, Republic of Korea, Japan, Mexico, United Kingdom, and United States.
  - A description of the usage of macro-prudential policies for a sample of 119 countries over the 2000-13 period is referenced (Cerutti, Claessens, and Laeven, March 2015).

### Framework of analysis: three interlocking objectives
- The common frame of analysis aligns with the three interlocking objectives set out in the August 2016 BIS/FSB/IMF G-20 report:
  - (1) Increasing the resilience of the financial system to aggregate shocks by building and releasing buffers to maintain financial intermediation under adverse conditions.
  - (2) Containing the build-up of systemic vulnerabilities over time by reducing pro-cyclical feedback between asset prices and credit and containing unsustainable increases in leverage, debt stocks, and volatile funding.
  - (3) Controlling structural vulnerabilities arising from interlinkages, common exposures, and the critical role of individual intermediaries that can render institutions “too-big-to-fail.”

### Key data categories and analytic focus
- Resilience of the financial system:
  - Holistic reviews encompassing deposit-takers and other financial institutions, inter-institution relationships, system structure and concentration, markets, financial infrastructure (clearing houses), and financial inclusion (particularly in developing countries).
  - Prudential supervisory data for deposit-takers remain essential for micro- and macro-prudential analysis.
- Systemic vulnerabilities from credit, debt, and asset prices:
  - Credit and debt data are central; fast credit growth can be an early warning indicator of financial crisis. (See Mathias Drehmann, BIS Quarterly Review, June 2013.)
  - Data on non-financial corporations (NFC) and households (HH) identify risks that can transmit to the financial sector.
  - Monitoring of connected, concentrated, or government-directed lending; growth of credit via FinTech is beginning to be assessed.
  - Asset prices monitored: residential and commercial real estate, equity and bond prices, land; growing interest in volatility measures.
- Structural vulnerabilities from interconnections and spillovers:
  - Increasing use of data to assess interconnections and spillovers among financial institutions, between financial and non-financial sectors, and with the rest of the world.
  - Complex second- and third-round linkages and common exposures make this a challenging area.
  - National FSA monitors international environment and capital flow impacts given potential spillovers from major economies.

### Cross-sectional vs time-series dimension; residence-based vs cross-border consolidated data
- Systemic risk has two dimensions:
  - Time dimension: build-up of risks over time.
  - Cross-sectional (structural) dimension: interconnectedness and distribution of risk at a point in time.
- Residence-based data:
  - Majority of datasets used by domestic policymakers for FSA are residence-based because domestic policy aims to protect residents and the domestic economy. This is primarily true for credit and debt, financial markets, interest rates, market infrastructure, inclusion, and domestic interconnectedness.
- Cross-border consolidated data:
  - Relevant for risks arising from domestically-owned institutions’ activities abroad; deposit-taker data are typically analyzed on a cross-border consolidated basis for micro- and macro-prudential purposes.
  - Basel standards aim to capture all banking and relevant financial activities within a group through consolidation to the greatest extent possible.
  - BIS IBS consolidated data provide a comprehensive picture of national lenders’ risk exposures and country risks and have longstanding use.
  - Enhancements to locational BIS IBS datasets include more granular information by nationality of the reporting bank.
- Importance of both views:
  - Residence-based data help analyze domestic interconnectedness and the relationship between domestic lending and funding.
  - Cross-border consolidated statistics capture nationality-based risks and foreign activities of domestically headquartered international banks.
  - NBFI data may be only available on a residence basis; FSA increasingly interested in borrowing by subsidiaries of resident entities located abroad (offshore borrowing), including U.S. dollar borrowing by foreign subsidiaries of emerging market NFCs.

### Data limitations and emerging gaps (introductory remarks)
- FSA is constrained by available data; policymakers have requested statisticians expand available information.
- The degree of market sophistication, range of financial institutions, and extent of interconnectedness affect the scope of data monitored for FSA across countries.
- Financial data for usefulness (US OFR, 2015): must have three attributes—(1) sufficient scope (comprehensive and granular), (2) high quality (comprehensive, accurate, timely), and (3) accessible (shared and secured). Identification of data gaps begins with deciding priority questions, the analytical framework, and the data needed to quantify it.
- The paper indicates a more detailed discussion of data used in FSA is provided in Appendix 1.

*Source: wp17153 - 2014 (IMF working paper content provided).*

### Appendix 2), policy makers at  the national and international level have continued to draw

### wp17153 - Appendix 2), policy makers at  the national and international level have continued to draw

### General observations on data for Financial Stability Analysis (FSA)
- Many needed data are already available to financial institutions and authorities, although coverage varies across countries.
- Since the GFC, statisticians and international initiatives (notably the G-20 DGI and the IMF's SDDS Plus) have expanded data availability for FSA.
- Benefits of implementing international initiatives accrue both to implementing economies and the broader international community.
- The G-20 DGI promoted closing gaps and strengthening datasets for monitoring:
  - risk in the financial sector (e.g., FSIs, securities issuance, credit default swaps data); and
  - domestic and cross-border risks (e.g., sectoral balance sheets, major cross-border surveys of the BIS and IMF).
- Remaining needs include enhancements in coverage, scope, quality, and consistency, plus some new data collection initiatives (for example, a granular dataset on globally systemically important financial institutions).
- Official statistics may be under-used; statisticians should better communicate the possibilities of available data (directly, indirectly via manipulation, or informational content relevant to FSA).
- Market/private sector and high-frequency data, including big data, are increasingly important complements to official statistics.

### Specific data gaps — Shadow banking
Findings
- Shadow banking performs credit and maturity transformation and can be systemically important, but is often less regulated and lacks access to deposit insurance and central bank facilities.
- Data identification and scale estimation of shadow banking activity are needed to understand entities involved and systemic vulnerabilities.
- Risks observed during the GFC include high leverage, maturity mismatches, and illiquidity; example: rapid runs on money market funds (MMFs) transmitted stress to broader markets and deposit-takers.
- Data on securities financing activities (repo, securities lending) are lacking, yet crucial to understand wholesale funding dependencies, interdependencies, collateral, and haircuts.
- Existing balance sheet and relevant data are typically collected under existing reporting requirements, with granularity and frequency varying across entities and jurisdictions; gaps are prominent for non-regulated entities.
- Sectoral balance sheets and flow of funds provide a good basis but limitations remain: need data by economic function, granular maturity and liquidity transformation, and foreign currency exposures.
- Cross-border consolidated data on a nationality basis are needed to complement residency-based data.

Suggested way forward
- Share experiences among statisticians, regulators, and users on compiling and analyzing shadow banking data to ensure comprehensive coverage and avoid duplication.
- Frequent dissemination of shadow banking data to facilitate timely assessment of system linkages and systemic risks.
- Support FSB efforts (annual monitoring reports and Shadow Banking Experts Group) and IAG Working Group work on macro-economic based data and more granular sub-sector/instrument coverage.
- FSB work to develop a regular flow of securities financing market data at national and global levels by end-2018 to illuminate size, composition, pricing, and risk profile.

### Assessment of capital flows
Findings
- Increased policy interest in financial stability implications of large swings in international capital flows; greater capital flow volatility can exacerbate transmission and spillovers.
- Balance of Payments (BoP) is a key source for cross-border flows but has gaps for detailed capital flow analysis:
  - Need for more timely BoP data (shorter reporting lag) and higher frequency indicators.
  - Identification of direction of flows between individual countries or groups of countries.
  - Separation of flows associated with non-financial corporate (NFC) activity from those of the financial sector in the BoP.
  - Increase number of countries disseminating breakdown of direct investment by geographical location, sector and currency (promoted via CDIS).
  - Increase number of countries disseminating breakdown of portfolio investment asset and liability data by geographical location and by currency (under DGI-2, sector breakdowns within the CPIS and move to quarterly reporting by 2019).
  - External balance sheet data needed on currency composition, remaining maturity of debt, and off-balance sheet items (contingent assets/liabilities, guarantees, lines of credit, hedging via derivatives).
- BIS and IMF to G-20 in 2016 emphasized BoP importance and identified these gaps.
- G-SIBs common data template could be aggregated to indicate cross-border capital flows from largest global banks and used more broadly for national banking system exposures.

Suggested way forward
- IMF BOPCOM could undertake a holistic review of cross-border exposures data to better leverage existing data for policy needs.
- Aggregate data from the G-SIBs common data template to provide early indications of cross-border flows and extend template use to national authorities for granular exposures/funding dependencies.

### Corporate borrowing
Findings
- BIS database shows NFC debt in major EMEs increased from less than 60 percent of GDP in 2006 to 110 percent at  end-2015.
- Data gaps for NFCs include:
  - foreign currency borrowing, particularly through offshore affiliates;
  - information on corporates’ risk exposures (leverage, debt maturity, foreign currency exposures, hedging activities).
- BIS IDS provides comprehensive issuance data for international debt securities (currency and maturity breakdowns) but lacks data on NFCs offshore foreign currency borrowing from deposit-takers.
- Offshore borrowing can cut across residence-based statistics: e.g., as of September 2015 offshore borrowing share of total borrowing via international debt securities by nationality NFCs was Chinese (93 percent), Brazilian (53 percent), Russian (45 percent).
- Residence-based measures can understate vulnerabilities; off-balance sheet activities and derivatives/hedging disclosures lack consistent international coverage.

Suggested way forward
- DGI-2 Recommendation 14 asks IAG to improve consistency and dissemination of NFC cross-border exposure data, including foreign affiliates and intra-group funding.
- Short-term: combine residence-based BoP data with BIS IBS and IDS to shed light on NFC cross-border exposures and evolution.
- Consider enhanced disclosures of financial hedges and derivatives positions, with detailed currency and maturity information, via improved accounting standards.

### Granular and micro-data
Findings
- FSA increasingly requires detailed, granular information (sector, country, currency dimensions) to allow flexible aggregation for multiple policy objectives.
- Initiatives for increased granularity include: common data template on G-SIBs, repo and securities financing transaction data, enhanced BIS IBS data, sectoral balance sheets, enhanced IMF CPIS.
- Sharing granular data can enable compilers to identify and resolve cross-institution and cross-country inconsistencies and reduce reporter burden.
- Micro data (supervisory) are valuable but face strict confidentiality constraints limiting sharing among agencies and with users.
- Granular information introduces data quality and consistency challenges for macro-prudential analysis.
- Macro-stress testing (especially top-down) would benefit from more detailed information.

Suggested way forward
- Continue work under DGI-2 Recommendation 20 to promote data sharing within jurisdictions and with other national authorities.
- International organizations should facilitate platforms to exchange experiences and help build trust given legal, structural, and cultural differences across jurisdictions.

### Real estate markets
Findings
- National/regional authorities emphasize monitoring residential and commercial real estate due to direct and indirect financial stability effects.
- Improvements since the GFC: DGI support, BIS public property price statistics database, inclusion of RPPI among core FSIs, RPPI in SDDS Plus.
- Datasets vary in quality and coverage; residential property coverage is relatively well covered in the BIS database but geographical/type coverage varies.
- Commercial Property Price Indices (CPPI) coverage has been expanding since 2016 but is limited in country coverage and differs by frequency and scope.
- Need additional housing-related indicators (price-to-rent, price-to-income ratios) to complement price indices.

Suggested way forward
- International guidance on RPPI compilation exists; CPPI conceptual guidance is in early stages.
- National efforts are key to ensure consistent data; ISWGPS (led by OECD, with IAG) is developing a list of other housing-related indicators under DGI-2 Recommendation 17.

### Insurance companies
Findings
- Insurance sector can pose systemic risks (AIG near-collapse); IAIS has identified G-SIIs with scheduled capital surcharges starting in 2022.
- Micro/supervisory data are more comprehensive for insurers than for other NBFIs, but gaps remain (liability structures, duration gap, common exposures, interconnections, cross-border links).
- Need better data on structure of liabilities (e.g., relative size of minimum guaranteed products and variable annuities within total liabilities for life insurers).

Suggested way forward
- DGI-2 Recommendation 4: FSB, with IMF and IAIS, to consider a common data template for G-SIIs; potential long-term collection of granular information via template and possible wider use for domestic/non-systemic insurers.

### Households
Findings
- FSA needs comprehensive household data: composition of assets and liabilities, household income, debt service payments.
- Growing interest in distributional information on consumption, saving, income, and wealth.
- Household surveys are key but costly; administrative data could complement surveys subject to confidentiality constraints.

Suggested way forward
- Share national experiences in compiling household data as part of sectoral accounts statistics.
- DGI-2 Recommendations 8 and 9: OECD, Eurostat, and ECB working with G-20 economies to encourage production and dissemination of distributional information based on the sectoral accounts framework.

### Summary table (Key data gaps and suggested way forward) — selected highlights
- Shadow Banking:
  - Gaps: heterogeneous institutions, lack of oversight, inconsistent definitions, insufficient economic-function data (leverage, liquidity, maturity, currency).
  - Way forward: FSB monitoring, IAG sector account work, sharing experiences, frequent dissemination.
- Capital Flows:
  - Gaps: timeliness, frequency, direction by country, separation of NFC flows, geographic/currency breakdowns, maturity/currency/exposure details.
  - Way forward: IMF BOPCOM holistic review; use G-SIBs common template aggregation.
- Corporate Borrowing:
  - Gaps: offshore foreign currency borrowing by NFCs, off-balance sheet exposures, hedging details.
  - Way forward: combine BoP with BIS IBS/IDS; improved hedge disclosures.
- Granular Data:
  - Gaps: confidentiality constraints, data quality/consistency.
  - Way forward: promote data sharing platforms; IO facilitation.
- Real Estate, Insurance, Households:
  - Gaps: property price coverage/quality, insurer liability/exposure detail, household distributional and debt-service data.
  - Way forward: national implementation, DGI-2 recommendations and templates.

### How can FSA data needs be addressed in macroeconomic statistical manuals?
Rationale
- Macroeconomic manuals (SNA, BPM, MFSMCG, External/Public Debt guides) should be reviewed to reflect increased policy focus on financial stability and support integrated datasets for policy.

Suggested enhancements (consistent with SNA framework and FSA needs)
A. Nonperforming loans (NPL) and provisions
- Current: SNA recommends memorandum items on NPLs; provisions are in central framework of MFSMCG.
- Options:
  - Introduce NPLs at nominal value into central framework for all sectors, with flows as other changes in volume of assets (OCVA).
  - Bring provisions for losses on nominal-valued assets into central framework (preferred by authors); record flows as OCVA to reflect profitability and capital effects more accurately.
- Rationale: Provisions in central framework better reflect timing/economic impacts than write-offs only.

B. Notional value of derivatives
- Market values are in central framework; notional values better capture risk exposures and transfers.
- Proposal: add notional values of financial derivative positions (by risk category and sector) as memorandum items for an economy-wide residence-based picture.

C. Remaining maturity
- Original maturity is standard; FSA prefers remaining maturity to assess near-term refinancing needs and maturity mismatches.
- Several manuals already include remaining maturity as memorandum/supplementary items; bringing remaining maturity into central framework would help FSA (including possibly a finer within-up-to-one-year breakdown at three months).

D. Foreign currency
- Existing items: MFSMCG sectoral domestic/foreign currency breakdown; BPM6 memorandum table by sector and major currency.
- Proposal: introduce foreign currency/domestic currency breakdown into central frameworks of SNA and BPM, combined with remaining maturity breakdowns; consider memorandum splits by major currency.

E. Sub-sector breakdown of NBFI
- 2008 SNA introduced seven NBFI sub-sectors; consider reviewing sub-sectoring to better meet FSA analytical needs, informed by FSB economic-function analysis of shadow banking (five functions).

F. Distinctions based on size
- SNA/BPM do not advise on entity size, but FSA needs activity breakdowns by household income level, non-bank financial corporate size (sales/assets/employment), and deposit-taker size (assets).
- Proposal: investigate compiling/disseminating size-based data, likely as memorandum items, leveraging DGI household distributional work.

### Concluding remarks
- Since the GFC, FSA governance and macro-prudential analysis have grown; this paper provides a holistic stock-take of datasets used for FSA.
- Common patterns of data use emerge across countries despite differences.
- Continued work is required on data relating to shadow banking, capital flows, corporate borrowing, and granular data, and on implementing enhancements to macroeconomic manuals (e.g., provisions, remaining maturity, foreign currency breakdowns) to support FSA without undermining conceptual frameworks.

*IMF Working Paper content (wp17153 - Appendix 2) as provided.*

### Appendix 1. Data Used in FSA

### Appendix 1. Data Used in FSA

### A) Increasing the resilience of the financial system
- Data scope and purpose
  - Size and structure of the financial system, including relative to GDP, compiled over time to detect shifts in structure and size (including regulatory-driven changes).
  - Aggregate balance sheet data for deposit-takers covering funding (including retail/wholesale split), assets by instrument/sector/maturity/currency, and capital, enabling calculation of the equity capitalization to book value ratio.
  - IMF list of FSIs covering capital adequacy, credit worthiness, profitability, and liquidity indicators are monitored.
- Deposit-taker specific datasets
  - Prudential supervisory data on individual institutions.
  - Separate indicators by domestic private, domestic state- and foreign-owned deposit-takers (preferably disclosing branches and subsidiaries separately).
  - Concentration measures and structural data (types of deposit-takers) to assess competition and systemic impact.
- Non-bank financial institutions (NBFIs)
  - Increasing interest in NBFI data, ideally broken down by type of activity.
  - Typical datasets: balance sheets, assets and liabilities with instrument/maturity/currency breakdowns for insurance companies, pension funds, MMF, investment funds (hedge and bond funds), mutual credit institutions, leasing companies, etc.
  - Leverage, liquidity, and profitability indicators; solvency measures for insurance companies; actuarial liabilities for defined pension funds.
- Financial markets
  - Monitoring of money markets, repurchase and security lending markets, debt securities, equity, derivatives, and foreign exchange markets.
  - Real-time price signals: interest rates and yield curves; spreads (domestic government bonds vs international benchmarks); credit default swap rates; exchange rates.
  - Market liquidity and depth: inventories scaled by trading volume (including hedges and offsetting positions) of dealers; liquidity indicators monitored to capture risk of sudden exits.
  - Market activity metrics: market capitalization, turnover, investor types and interrelationships, collateral reuse and haircuts, gross short positions by participant type, on- and over-the-counter derivatives activity.
- Financial market infrastructure and inclusion
  - Data on payments systems, clearing houses, Central Counter-parties (CCP): scale of activity (including scale and timing of intra-day settlements), margining requirements, and capitalization.
  - Financial inclusion indicators: access to banks, Automated Teller Machines (ATM), Mobile Money Accounts; supply of financial services to households and associated risk indicators.

### B) Containing the build-up of systemic vulnerabilities: Credit, debt and asset prices
- Credit-related datasets
  - Granular credit data from deposit-takers to capture total credit, growth, size relative to GDP, currency composition, maturity profile, and interest rates.
  - Distributional data: sector, industry, region; provision by type (loan, securities, trade credit, etc.); ownership of lending institutions (private domestic, domestic state-owned, foreign-owned).
  - Household credit types: mortgage, credit card, student loans, etc.; commercial real estate credit (including real estate companies); collateralized vs non-collateralized loans.
  - Asset-quality measures: nonperforming loans and provisions.
  - Monitoring of deposit-takers connected lending, concentrated lending, and directed lending as percentage of total loans.
  - Monitoring of FinTech-originated credit channels (e.g., peer-to-peer lending) where relevant.
  - For developing economies: credit to the private sector as percentage of GDP and financial inclusion indicators.
- Debt-related datasets
  - Total debt size and composition (instruments, currencies, maturity) relative to GDP; debtor ability to service debt.
  - Government debt data at nominal and market values due to its central role in financial markets and sovereign risk assessment.
  - Sectoral depositor composition and scale/composition of wholesale borrowing to assess funding source diversification and concentration risks.
  - Remaining maturity and foreign currency breakdowns to detect currency and maturity mismatches.
  - Leverage measures including off-balance sheet exposures (financial derivatives with add-on factors for potential future exposure) across sectors; “net debt” measures for households and government.
- Non-financial corporate (NFC), household (HH) and government data
  - Comprehensive balance sheet data for NFC and HH (assets and liabilities in domestic and foreign currencies), equity for NFC, and net worth.
  - NFC indicators: profitability (return on assets), income and debt measures (interest coverage ratio, debt service ratio, interest exposure fixed/variable), industry and size breakdowns, measures of “risky companies.”
  - HH indicators: disposable income, debt service to disposable income, distributional breakdowns, identification of “risky households” via debt service ratios and negative net financial assets, household financial and non-financial assets and liquidity.
  - Government indicators: public sector arrears to private suppliers and contingent liabilities as transmission channels to corporate and financial sector health.
- Asset price datasets
  - Real estate prices (residential, commercial, land); related indicators: transaction volume, price-to-rent, price-to-income ratios (including regional breakdowns), commercial property yields, vacancy rates.
  - Financial market asset prices: equity and bond prices, equity price components by sector (commodity-related, financial-related, foreign-demand related), and volatility measures (intra-day and over time), including VIX indices for equity prices, interest rates, exchange-traded funds, and currency-related volatility.

### C) Structural vulnerabilities within the financial system: Financial interconnections and spillovers
- Interconnections data and rationale
  - Sectoral balance sheets and to-whom/from-whom datasets to map domestic and cross-border interconnections.
  - Major cross-border internationally coordinated surveys used: BIS IBS, IMF CPIS, and CDIS.
  - Focus on debtor-creditor relationships: who owes what to whom at national and sectoral levels; ownership structures among financial institutions and between financial institutions and non-financial corporations.
- Cross-border and consolidated reporting
  - Cross-border assets and liabilities data on a granular basis (including by individual deposit-taker) with instrument, country, sector, and currency breakdowns.
  - Relevance of residence-based and cross-border consolidated (nationality) approaches.
  - G-SIB (Global Systemically Important Financial Institutions) data: extra capital charges for G-SIBs and collection of data under a common template on relationships among G-SIBs and their exposure to national sectors and markets to identify common exposures.
  - Domestic Systemically Important Financial Institutions considerations similar at the national level.
- External finance and capital flow monitoring
  - Data on residents’ borrowing channels: (1) directly from abroad; (2) from domestic branches of foreign deposit-takers; (3) through foreign subsidiaries of resident entities.
  - Monitoring of reliance on wholesale borrowing from abroad as an early indicator of unsustainable credit growth.
  - Balance of payments data, bond yields correlations, GDP and industrial production, international investment position (IIP) data, and external debt data (short-term, government debt, corporate debt securities by currency and by country of creditor) for spillover and vulnerability analysis.
  - Global liquidity indicators and drivers (as of the document’s analysis) relevant to domestic macroprudential policy; BIS global liquidity indicators draw on bank credit data from the IMF, BIS locational banking statistics, and BIS debt securities data.
- Domestic consideration of international environment
  - National FSAs monitor foreign economies using real and financial indicators and commodity prices where relevant (e.g., oil) to assess spillover risks.

*Source: Appendix 1. Data Used in FSA, wp17153.*

### Appendix 2. What has been the Response of Statisticians to the Growing Interest in

### Appendix 2. What has been the Response of Statisticians to the Growing Interest in FSA?

### G-20 Data Gaps Initiative (DGI) — overview and purpose
- Launched in response to data gaps identified by policy makers and analysts in the immediate aftermath of the GFC; primarily focused on financial stability policy needs.
- Now in its second phase (DGI-2) and consists of 20 recommendations that strengthen and enhance existing statistical initiatives and, in some instances, initiate new statistical collections.
- Overseen by the IAG and reported annually to the G-20 Finance Ministers and Central Bank Governors; IMF and FSB Secretariat provide progress reports.

### Key datasets and statistical efforts promoted under the DGI
- Financial Soundness Indicators (FSIs)
  - Developed to meet FSA needs following the Asian crisis of the late 1990s; list updated in 2013 following a global consultation.
  - Focused primarily on deposit-takers; macro view of supervisory-type data covering capital, profitability, asset quality, liquidity, and market risk sensitivity.
  - Data largely drawn from supervisory balance sheet data and income statements, compiled for deposit-takers.
  - Updated FSI list includes: size and investments of NBFI, solvency and liquidity indicators for NFCs, debt to disposable income ratio for HH, and as a core indicator, residential real estate prices (some countries reporting).
  - Number of countries reporting FSI data to the IMF increased to over 120 by 2016.
  - A table of FSIs is typically presented in FSAP assessments and included in the GFSR.
- Concentration and distribution measures (CDM)
  - Can identify vulnerabilities developing within the deposit-taking sector that aggregate data may disguise.
  - IMF undertook a voluntary pilot project on CDMs with member countries based on a selected number of FSIs.
  - DGI-2 will investigate whether to collect such data on a regular basis.
- Debt Statistics
  - Conceptual guides developed in the early 2000s: External Debt Statistics Guide (2013) and Public Sector Debt Statistics Guide (2011).
  - Guides provide internationally agreed measurement guidance including foreign currency, debt service, remaining maturity, and ultimate risk concepts for external debt.
  - DGI recommended reporting public sector debt data to the World Bank (host)/IMF/OECD quarterly public sector debt statistics hub.
  - By 2016 over 70 economies reported data to the public sector debt hub.
  - Over 120 countries report data consistent with the External Debt Statistics Guide to the World Bank (host)/IMF quarterly joint external debt hub.
- Securities statistics
  - 2015 Working Group on Securities Databases (WGSD) published a Handbook on Security Statistics (Handbook) with presentation tables and classifications to assist compilation and dissemination.
  - DGI-2 sets reporting of debt securities issuance data to the BIS on a quarterly frequency (sector, currency, type of interest rate, original maturity) as an objective for G-20 economies.
- Real estate prices
  - DGI recommended a two-pronged approach: BIS and member central banks to disseminate available residential and commercial real estate prices — by 2016, 58 countries reported data.
  - ISWGPS to publish robust methodology; a Handbook on Residential Property Price Indices was published in 2013 and guidance on compiling commercial real estate price indices to be prepared.
- Derivative and repo statistics
  - BIS enhanced data on credit derivatives after the GFC.
  - FSB created expert groups to aggregate micro-data on derivative markets and on repo and security lending markets to support financial stability risk analysis.
- Shadow banking
  - FSB has produced an annual report on shadow banking since 2011 primarily using national accounts-based data.
  - National-accounts data provide a broad estimate but are insufficient for FSA; need refined disaggregation by economic functionality and greater focus on risk analysis.
  - FSB, with member countries’ help and supported by DGI-2, is refining estimates to better meet FSA needs.
- Sectoral accounts
  - Comprehensive sectoral balance sheet data are essential for FSA to overview developments across the whole economy and compile ratios such as debt to equity (leverage) and financial assets/liabilities of individual sectors to total assets/liabilities.
  - To-whom from-whom data in sectoral accounts provide valuable information on domestic interconnections.
  - Dissemination of a comprehensive set of sectoral accounts is highlighted as a key contribution national account statisticians could make to support FSA.
  - An extensive sector balance sheet template was internationally agreed in 2012 as a longer-term objective for IMF and OECD economies to work towards.
- Distributional data on household income, consumption and wealth
  - Work by the OECD in close cooperation with Eurostat and the ECB on distributional data can help identify inequalities that could impact FSA.
- International Investment Position (IIP)
  - DGI promoted quarterly IIP data; quarterly IIP became a required item in the Special Data Dissemination Standard (SDDS) in September 2014.
  - DGI supports improvements in availability of foreign currency data, including promoting foreign currency and remaining maturity enhancements to the IIP included in BPM6.
- International Banking Statistics (IBS)
  - BIS IBS data exist since the 1960s; data have been enhanced over time as analytical needs emerged.
  - In 2012 the Committee on the Global Financial System (CGFS) approved major enhancements to close information gaps for monitoring and responding to financial stability risks.
  - BIS and its central banks started publishing data with the new enhancements by 2015 and intend to disseminate more data depending on reporting countries’ progress.
  - Enhancements include expanding coverage of banks' balance sheets to include domestic positions and international activities and providing more information on sectors of banks’ counterparties, including exposures to and reliance on funding from non-bank financial counterparts.
- Global Flow of Funds
  - DGI does not have a specific recommendation for a global flow of funds but covers most datasets needed to compile such a matrix (e.g., more frequent CPIS with sector breakdowns and compilation of both inward and outward CDIS in DGI-2).
  - A global flow of funds concept has been developed to allow analysis of financial interconnections within and across borders, but the work remains in an embryonic stage.
- Global Systemically Important Banks (GSIBs)
  - In response to two DGI recommendations, two unique datasets based on common templates have been developed to monitor bilateral institutional links of GSIBs and their exposures to national markets and sectors.
  - Work led by the FSB in close consultation with the IMF; a data hub at the BIS collects and processes national data in a confidential setting.
  - DGI-2 investigates the possibility of a common data template for global systemically important NBFI starting with insurance companies.
- Granular data
  - Increasing demand for granular data (e.g., loans by deposit-takers) to identify emerging risks and allow many disaggregations as policy needs change.
  - Granular data can reduce reporting costs by limiting the need to compile multiple disaggregations over time, but confidentiality issues are important.
  - DGI-2 includes a recommendation to investigate possibilities for granular data, including sharing data across borders.

### Special Data Dissemination Standard Plus (SDDS Plus)
- Established by the IMF in 2014 as the third tier of the IMF’s data dissemination standards initiative.
- Draws heavily on DGI datasets with the objective to “guide member countries on the provision of economic and financial data to the public in support of domestic and international financial stability.”
- Covers nine datasets that provide information on the real and government sectors and most extensively on the financial and external sectors.
- The nine datasets are: sectoral balance sheets, general government operations and debt, other financial corporations survey, FSIs, debt securities, Coordinated Portfolio and Direct investment surveys, and the currency composition of official foreign exchange reserves (COFER) survey.

### Data availability and dissemination tools
- IMF paper 2012 Review of Data Provision to the Fund for Surveillance Purposes contained a list of data sources relevant for FSA; many of these data sources are cited as relevant in Appendix 8.

*Source: Appendix 2 of wp17153 - Appendix 2. What has been the Response of Statisticians to the Growing Interest in FSA?*

### References

### wp17153 - References

### Major subjects covered
- Macroprudential policy design, implementation, and effectiveness.
- Data initiatives, gaps, and enhancements for financial surveillance and statistics.
- Shadow banking, securities financing, and OTC derivatives data aggregation.
- Stress testing methodologies, liquidity risk management, and financial stability assessments.
- Global financial regulatory reforms and implementation (G-20, FSB, BIS, IMF).
- Country-level FSAPs and financial stability reviews.

### Key references and contributions (selected by theme)
- Macroprudential policy and credit cycles:
  - Cerutti, Eugenio; Stijn Claessens; and Luc Laeven: "The Use and Effectiveness of Macroprudential Policies: New Evidence," IMF Working Paper 15/61, March 2015.
  - Dell’Ariccia, Giovanni; Deniz Igan, Luc Laeven, and Hui Tong with Bas Bakker and Jerome Vandenbussche: "Policies for Macrofinancial Stability: How to Deal with Credit Booms," IMF Staff Discussion Note, June 2012.
  - Drehmann, Mathias: "Total credit as an early warning indicator for systemic banking crises," BIS Quarterly Review, June 2013.
  - BIS/FSB: "Summary: Joint CGFS – FSB-SCAV workshop on risks from currency mismatches and leverage on corporate balance sheets," 2014.

- Data initiatives, gaps, and statistical frameworks:
  - FSB/IMF, September 2015, Sixth Progress Report on the G-20 Data Gaps Initiative.
  - FSB/IMF, September 2016, First Progress Report on the Second Phase of the G-20 Data Gaps Initiative.
  - Inter-Agency Group on Economic and Financial Statistics, "Consolidation and corporate groups: an overview of methodological and practical issues," October 2015.
  - Working Group on Securities Databases, Handbook on Security Statistics, 2015.
  - IMF, 2012 Review of Data Provision to the Fund for Surveillance Purposes, August 2012.
  - TFFS, 2014, External Debt Statistics Guide.

- Shadow banking, securities financing, and derivatives:
  - IMF, Global Financial Stability Report, Chapter 2: "Shadow Banking Around the Globe: How Large, and How Risky?" October 2014.
  - FSB, "Strengthening Oversight and Regulation of Shadow Banking: Policy Framework for Addressing Shadow Banking Risks in Securities Lending and Repos," August 2013.
  - FSB, Global Shadow Banking Monitoring Report, 2015.
  - FSB, "Standards and Processes for Global Securities Financing Data Collection and Aggregation," November 2015.
  - FSB, "Feasibility study on approaches to aggregate OTC derivatives data," September 2014.

- Stress testing, liquidity, and risk aggregation:
  - IMF, "Macrofinancial Stress Testing—Principles and Practices," 2012.
  - Jobst, Andreas, Li Lian Ong, and Christian Schmieder, "Macroprudential Liquidity Stress Testing in FSAPs for Systemically Important Financial Systems," IMF Working Paper 17/102.
  - Basel Committee on Banking Supervision, 2012, "Principles for effective risk data aggregation and risk reporting."
  - Basel Committee on Banking Supervision, "Principles for Sound Liquidity Risk Management and Supervision," September 2008.

- International banking, cross-border flows, and currency mismatches:
  - Avdjiev, Stefan; McGuire, Patrick; and Wooldridge, Philip, "Enhanced data to analyse international banking," BIS Quarterly Review, September 2015.
  - McGuire, Patrick and von Peter, Goetz, "The US dollar shortage in global banking and the international policy response," BIS Working Papers No. 291, October 2009.
  - Chui, Michael, Emese Kuruc, and Philip Turner, "A new dimension to currency mismatches in the emerging markets: nonfinancial companies," BIS Working Papers, No. 550, March 2016.
  - Tarashev, Nikola, Stefan Avdjiev, and Ben Cohen, "International capital flows and financial vulnerabilities in emerging market economies: analysis and data gaps," BIS note submitted to the G-20 International Financial Architecture Working Group, August 2016.

- Financial stability assessments, FSAPs, and institutional views:
  - IMF, "The Financial Sector Assessment Program (FSAP), Factsheet," 2016.
  - IMF, 2014, Republic of Korea FSAP.
  - IMF, 2014 Canada FSAP.
  - Frecaut, Oliver, "A National Wealth Approach to Banking Crises and Financial Stability," IMF Working Paper 16/128.

- Regulatory frameworks, disclosure, and capital standards:
  - Basel Committee on Banking Supervision, "Scope of Application, International Convergence of Capital Measurement and Capital Standards," June 2006.
  - Basel Committee on Banking Supervision, "Revised Pillar 3 disclosure requirements," January 2015.

- Research on crises, history, and conceptual definitions:
  - Kindleberger, Charles, Manias, Panics and Crashes, A History of Financial Crises, 1978.
  - Reinhart, Carmen M. and Kenneth S. Rogoff, "This time is different: A panoramic view of eight centuries of financial crises," 2009.
  - Schinasi, Garry, "Defining Financial Stability," IMF Working Paper 04/187.

### Notable working papers, reports, and datasets referenced (exact identifiers)
- IMF Working Paper 15/61; IMF Working Paper 16/110; IMF WP 16/26; IMF Working Paper 15/146; IMF Working Paper 06/163; IMF Working Paper/12/163.
- BIS Working Papers No. 309; No. 291; No. 550; No. 587; No. 588; No. 480; No. 205.
- FSB reports: August 2013 policy framework; September 2014 OTC derivatives feasibility study; November 2015 standards for securities financing; 2015 CCP Work Plan.
- IMF Policy Papers: September 2015 "Monetary Policy and Financial Stability"; October 2016 "Tax policy, leverage and macroeconomic stability"; December 2016 "Capital Flows—Review of Experience with the Institutional View"; January 2017 "Macroeconomic Developments and Prospects in Low-Income Developing Countries—2016."

### Cross-cutting policy implications and analytical focuses (as represented in references)
- The need for enhanced, harmonized data for cross-border banking, securities financing, and derivatives to support surveillance and stress testing.
- Use of macroprudential instruments to address credit booms, leverage, and systemic risk in both banking and nonbank sectors.
- Strengthening disclosure (Pillar 3), risk data aggregation, and liquidity risk management to improve financial resilience.
- Monitoring and addressing shadow banking activities, securities lending, and repo markets to mitigate systemic vulnerabilities.
- Integration of macrofinancial stress testing into surveillance and FSAPs for systemically important financial systems.

*References list from wp17153 - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2017/wp17153.pdf_