## EXECUTIVE SUMMARY — _cr14347

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### Macroprudential policy: principal tasks and importance
- Three interlocking tasks:
  - Contain the build-up of macrofinancial imbalances associated with credit booms and asset price bubbles (important in Denmark where the space for monetary policy action is limited).
  - Control structural vulnerabilities from size and interconnectedness within the financial sector and from interlinkages between the financial sector and other sectors.
  - Increase the resilience of the financial system to aggregate shocks by building buffers enabling institutions to continue credit provision under adverse conditions.
- Early development and implementation of macroprudential tools are essential because risks can build up rapidly even when vulnerabilities appear contained.

### Institutional framework adopted in 2013–2014 (SRC, MoBG, DN, DFSA)
- Systemic Risk Council (SRC) established in 2013:
  - Composition: representatives from Danmarks Nationalbank (DN), Danish Financial Supervisory Authority (DFSA), relevant ministries, and independent experts.
  - Chair: Chairman of DN's Board of Governors; DN hosts the secretariat; DFSA and ministries participate in secretariat.
  - Tasks: identify and monitor systemic risks and issue observations, warnings, and recommendations to DFSA and the government.
  - Transparency/accountability: “comply or explain” rule; abstention rule for government representatives and DFSA on recommendations to government.
- Designated macroprudential authority and decision rights:
  - Minister of Business and Growth (MoBG) appointed as designated macroprudential authority; decision-making power on most macroprudential instruments currently lies with MoBG.
  - DFSA competent authority for Pillar 2 and measures under CRR Articles 124 and 164.
  - MoBG is designated authority for buffers and national flexibility under CRR Article 458 (including CCB, Systemic Risk Buffer, G-SII-buffer).

### D-SIFI identification, systemic importance, and capital buffers
- D-SIFI identification criteria (legal thresholds):
  - Size of the balance sheet > 6.5 percent of Denmark’s GDP.
  - Loans > 5 percent of total sector loans.
  - Deposits > 5 percent of total sector deposits.
  - Institution must exceed one limit for two consecutive years to be defined as a SIFI.
- First D-SIFI designations (June 2014): six largest banking groups
  - Danske Bank
  - Nordea Bank Denmark
  - Nykredit
  - Jyske Bank
  - Sydbank
  - DLR Kredit
- Quantitative indicators (2013 consolidated level, selected):
  - Danske Bank — Total assets in percent of GDP: 160.2; Loans in percent of the total loans of the sector: 30.4; Deposits in percent of the total deposits of the sector: 35.9
  - Nykredit — Total assets in percent of GDP: 76.3; Loans in percent of the total loans of the sector: 32.7; Deposits in percent of the total deposits of the sector: 4.6
  - Nordea Bank Danmark — Total assets in percent of GDP: 44.8; Loans in percent of the total loans of the sector: 16.0; Deposits in percent of the total deposits of the sector: 22.0
  - Jyske Bank — Total assets in percent of GDP: 14.1; Loans in percent of the total loans of the sector: 3.4; Deposits in percent of the total deposits of the sector: 8.9
  - Sydbank — Total assets in percent of GDP: 8.0; Loans in percent of the total loans of the sector: 1.8; Deposits in percent of the total deposits of the sector: 5.4
  - DLR Kredit — Total assets in percent of GDP: 7.9; Loans in percent of the total loans of the sector: 3.5; Deposits in percent of the total deposits of the sector: 0.0
- SIFI capital surcharges and phasing:
  - SIFI surcharges (CET1) ranging from 1–3 percent of risk weighted assets depending on systemic importance (phase-in starting 2015 through 2019).
  - Parliament reduced an initial recommendation of 3.5 percent for the most systemic institution to an upper limit of 3 percent.
  - Combined capital requirement for SIFIs from 2019: at least 11.5–13.5 percent of risk-weighted assets, comprising:
    - Pillar I minimum: 8 percent.
    - Capital conservation buffer: 2.5 percent.
    - Systemic risk buffer: 1–3 percent.
  - Up to 10 percent of total requirement to be comprised of CET1 (excluding the Countercyclical Capital Buffer and Pillar 2 requirements).
  - DFSA published institution-level Pillar II requirements: range from 1.8 percent for Jyske to 2.8 percent for Nordea; current averages: just below an average of 2 percent for SIFIs and more than 3 percent for other banks and MCIs.
  - SIFI Committee recommended a “crisis management buffer” of 5 percent of risk weighted assets (possibly including up to 3.5 percent in Tier 1/2), to be established over a three-year period starting in 2020 (decision postponed).

### Countercyclical Capital Buffer (CCB) framework and implementation
- Phasing schedule for CCB (national implementation):
  - 2015: up to 0.5 percent.
  - 2016: up to 1 percent.
  - 2017: up to 1.5 percent.
  - 2018: up to 2 percent.
  - 2019: up to 2.5 percent.
- Recognition of foreign buffers: buffer rates set in other countries where Danish institutions have exposure will be recognized up to 2.5 percent from 2015.
- Operational design and indicators:
  - Core activation/calibration indicator: credit-to-GDP gap (one-sided Hodrick-Prescott filter) and BCBS formula for mapping gap to buffer.
  - MoBG will take into account: deviation of credit-to-GDP ratio from its long term trend and other indicators/factors; MoBG may act on SRC recommendation and seek DFSA input.
  - Additional indicators for release phase: growth rate of new loans, market-based measures (credit spreads), measures of asset quality (NPLs).
- Limitations of CCB and need for complementary tools:
  - CCB is a blunt, uniform tool; may be slow/react poorly to segment-specific risk build-ups and less effective where banks hold voluntary buffers or generate capital from earnings.
  - Complementary instruments recommended: targeted higher risk weights, sectoral capital requirements, higher provisioning, LTV and DSTI limits, and legal use of CRR Articles 124, 164, and 458.

### Monitoring, analytics, and routine surveillance tools
- Routine monitoring:
  - Quarterly broad-based scans using a risk dashboard tied to ESRB intermediate objectives (mitigate excessive credit growth and leverage; mitigate maturity mismatch and illiquidity; limit exposure concentration; limit systemic impact of misaligned incentives; strengthen financial infrastructure resilience).
  - Short surveillance notes, updated risk dashboard, and ad-hoc notes produced for every SRC meeting.
  - DN stress tests of largest banks every six months; event/scenario analyses; international/national reports.
- Current limitations:
  - Surveillance framework operational for about one year; no econometric models or larger statistical frameworks yet integrated with the dashboard.
- Suggested additional analytical tools:
  - Country Financial Stability Map (Spider-gram), risk heat maps, measures of interconnectedness, distress dependence, joint probability of distress (JPoD), Banking Stability Index (BSI), and CCA-GVAR cross-sectoral analyses.

### Heat maps and selected empirical indicators (dec-06 to dec-13 series, selected rows)
- All Banks (selected rows):
  - Deposit/ Loan (FSI definition): 31.5 31.1 29.1 30.1 30.6 31.3 31.2 29.0
  - Deposit/ Loan (authorities' definition): 26.4 30.0 32.7 34.5 33.0 32.8 32.9 33.8
  - FX Liabilities/ Total Liabilities: 25.7 29.4 29.0 26.5 26.2 25.7 22.7 30.8
  - Capital / Assets: 5.8 6.3 5.5 5.5 5.4 5.1 5.3 7.1
  - Return on Assets: 0.30 0.16 -0.25 -0.08 0.04 -0.02 0.04 0.06
  - Level of NPLs: 0.7 0.6 2.4 4.9 4.7 5.4 5.1 5.5
- Commercial Banks (selected rows):
  - FX Liabilities/ Total Liabilities: 6.8 9.8 7.9 10.6 11.8 11.9 10.5 13.7
  - Capital / Assets: 4.0 5.7 4.9 3.1 3.0 2.0 2.1 4.7
  - Return on Assets: 0.20 0.11 -0.03 0.02 0.05 0.04 0.05 0.05
  - Level of NPLs: 0.1 0.1 0.4 1.0 1.2 1.1 2.1 1.7
- Mortgage Banks (selected rows):
  - Deposit/ Loan (FSI definition): 74.4 71.2 65.2 73.9 76.1 83.5 86.2 79.9
  - Deposit/ Loan (authorities' definition): 73.4 74.1 79.4 89.4 89.5 87.7 90.9 95.9 105.2
  - FX Liabilities/ Total Liabilities: 42.4 45.8 46.5 42.5 42.5 41.4 41.0 36.6 47.4
  - Capital / Assets: 7.4 6.8 6.0 7.7 7.8 8.0 8.4 9.2
  - Level of NPLs: 1.5 1.2 3.8 7.0 7.9 7.9 8.3 8.7
- Interpretation highlights:
  - Deposit-to-loan: higher ratio = lower liquidity risk; authorities’ consolidated deposit/loan is now in the low range after being medium in recent years; commercial banks’ solo measure indicates higher liquidity risk when including covered-bond-funded loans.
  - FX exposures: commercial banks’ FX loans and liabilities exceed a 40 percent threshold in some measures, but FX risk is limited because most FX loans are in Euros and the DKK is pegged to the Euro.
  - Asset quality: impaired loan ratio (authorities’ definition) in medium to high vulnerability range; 90-day past-due NPL ratios (FSI definition) are lower and improved over time; impaired loan ratio for MCIs increased by 48 percent y/y at end-2013 though level remains low.
  - Cross-bank variation: medium-sized and small banks show higher impaired loan ratios and sharper increases than large banks.

### Systemic importance, interconnectedness, and TITF subsidy (Danske example)
- Interconnectedness and market-based measures:
  - Econometric distress dependence (Segoviano and Goodhart 2009) for four D-SIFIs shows conditional probabilities of distress differ across pairs; if Nordea defaults, higher probability of Danske defaulting compared to the reverse.
  - JPoD typically follows average unconditional expected default frequency (EDF).
  - Banking Stability Index (BSI) measures expected number of banks becoming distressed given at least one is distressed.
- Implicit government subsidy for Danske (Appendix III):
  - Contingent Claims Approach (CCA): estimated subsidy at 80 bps equivalent to US$15 billion (latest); historical peak 86 bps (US$17bn) around Lehman crisis.
  - Ratings-based approach: 2012 subsidy US$4.8 bn; 2009 peak 37 bps (US$6.8 bn); current scenario estimate about 17 bps but can increase up to 76 bps in distress scenarios.
  - Policy implication: intensified supervision, increased loss-absorbency, and an effective resolution regime for D-SIBs required to catalyze reversal of implicit subsidies.

### Cross-sector and cross-border linkages (CCA-GVAR and network analysis)
- CCA-GVAR findings (within Denmark and cross-border):
  - Modeled variables: bank, corporate, sovereign credit spreads; credit growth; real GDP.
  - Sample: Danske (bank) and 111 corporates in Denmark.
  - Examples of estimated responses:
    - 50 basis point shock to sovereign credit spreads increases Danske Bank credit spreads by 29 basis points.
    - 14 basis point shock to corporate spreads increases Danske Bank credit spreads by 14 basis points.
    - One standard deviation shock to GDP increases Danske Bank credit spreads by 23 basis points.
  - Cross-border: a one standard deviation shock to Denmark banking sector (87 basis points increase in credit spreads) increases average credit spreads in Norway and Sweden by 19 basis points and in other countries in the model by 26 basis points (model covers 16 countries).
- Network analysis (flow of funds, 2013Q4, percent of GDP):
  - Total gross claims on the corporate sector: 442 percent of GDP.
  - Total gross claims on banks: 417 percent of GDP.
  - Net assets highest for households: 143 percent of GDP.
  - Financial sector sizes: Banks gross financial assets 422 percent of GDP; Insurance and pension funds 170 percent of GDP; Other financial intermediaries 161 percent of GDP.
  - Largest linkages: interbank linkages 110 percent of GDP; linkage between insurance & pension funds and OFIs 52 percent of GDP.
  - Relative claims: insurance corporations and pension funds hold 85 percent of their liabilities owed to households; banks hold 90 percent of household liabilities (representing 30 percent of bank assets).

### Suggested additional indicators, tools, and analytics
- Expand analytical toolkit (short term priority for DN):
  - Country Financial Stability Map (spider-gram), risk heat maps, measures of interconnectedness, econometric models, stress-testing, event/scenario analysis.
- Introduce targeted macroprudential instruments (short term priority for DN, DFSA):
  - Limits on loan-to-value (LTV) ratios and debt service-to-income (DSTI) ratios.
  - Higher risk weights on lending to particular sectors; sectoral capital or provisioning measures.
  - Improve borrower- and loan-level data collection: distributions of LTVs and DSTIs across loans, property types, borrower categories, and over time.
- Institutional review (medium term priority):
  - Review the appointment of the government (MoBG) as the designated authority for most macroprudential instruments and assess whether decision-making powers should be reallocated after SRC evaluation (first evaluation planned in 2016).
  - Near-term priority: ensure coordination among agencies and keep independent experts apprised.

### Table of Recommendations on Macroprudential Policy (as presented)
- Expand the range of analytical tools used to identify and monitor systemic risk (DN) — Priority: Short term
- Explore new instruments capable of addressing time-varying systemic risk, such as limits on LTV and debt service to income (DSTI) ratios (DN, DFSA) — Priority: Short term
- Review the experience with the institutional arrangements, especially the appointment of the government as the designated authority for most macroprudential instruments — Priority: Medium term

Note on timing convention:
- Short-term indicates within 18 months; medium-term indicates from 18 months to three years.

*Source: IMF staff report content unit _cr14347.*

### EXECUTIVE SUMMARY ___________________________________________________________________________ 5

### EXECUTIVE SUMMARY

### Macroprudential policy: principal tasks and importance
- Macroprudential policy has three interlocking tasks:
  - Contain the build-up of macrofinancial imbalances associated with credit booms and asset price bubbles, a function which is particularly important in Denmark, where the space for monetary policy action is limited.
  - Control structural vulnerabilities that arise from size and interconnectedness within the financial sector, and from interlinkages between the financial sector and other sectors of the economy.
  - Increase the resilience of the financial system to aggregate shocks by building buffers which enable financial institutions to continue their credit-providing function under adverse economic conditions.
- Even when vulnerabilities appear contained and a crisis distant, risks can build up rapidly, so early development and implementation of macroprudential tools are essential.

### Institutional framework adopted in 2013–2014
- Denmark adopted an institutional framework for macroprudential policy in 2013 that includes a Systemic Risk Council (SRC).
  - SRC brings together representatives from Danmarks Nationalbank (DN), the Danish Financial Supervisory Authority (DFSA), relevant government ministries, and independent experts.
  - The Chairman of the DN's Board of Governors heads the SRC and the central bank hosts the secretariat. The DFSA and other ministries represented in the SRC participate in the secretariat.
  - SRC tasks: identify and monitor systemic financial risks and issue observations, warnings, and recommendations to the DFSA and the government.
- Decision-making power on most macroprudential instruments currently lies with the Minister of Business and Growth (MoBG), appointed as the designated macroprudential authority.
- The SRC features transparency and accountability arrangements, including a “comply or explain” rule and an abstention rule for government representatives and the DFSA on recommendations to the government.

### D-SIFI identification and capital buffers
- Domestic systemically important financial institutions (D-SIFIs) have been identified and capital surcharges are being imposed.
  - Six largest banking groups designated as D-SIFIs in June 2014: Danske Bank, Nordea Bank Denmark, Nykredit, Jyske Bank, Sydbank, and DLR Kredit.
  - Starting in 2015 and following a phase-in period until 2019, D-SIFIs will be subject to higher capital requirements ranging from 1–3 percent of risk weighted assets, depending on systemic importance.
  - Countercyclical capital buffer (CCB) framework will be phased in starting with an upper bound of 0.5 percent in 2015 increasing to 2.5 percent in 2019. From 2020, the buffer could be further increased based on the authorities’ assessment.

### Recommendations to strengthen the macroprudential framework
- Expand the range of analytical tools used to identify and monitor systemic risk (DN).
  - Current SRC material includes a risk dashboard and illustrations of macroprudential risks under each intermediate target over time, plus notes on specific topics.
  - Other possible tools: financial stability spidergram showing changes in overall risks over time; risk heat maps (based on thresholds for various indicators); measures of interconnectedness across financial institutions and economic sectors.
- Introduce new policy instruments to address time-varying systemic risk (DN, DFSA).
  - In addition to the expected implementation of the CCB framework in January 2015, authorities should explore limits on loan-to-value (LTV) ratios and debt service-to-income (DSTI) ratios, and imposing higher risk weights on lending to particular sectors.
  - Improved data collection is warranted on the distribution of LTVs and DSTIs across loans, types of property, categories of borrowers, and over time to inform calibration and activation.
- Review institutional arrangements, especially the appointment of the government as the designated authority for most macroprudential instruments.
  - Given decision-making power lies with the government (rather than an institution with operational independence), there is greater risk that political considerations could delay necessary macroprudential action.
  - Denmark is one of only three countries in Europe where the designated authority is the government. After about a year, when the SRC is to be evaluated, authorities are encouraged to assess the effectiveness of the current system, including this appointment.

Table of Recommendations on Macroprudential Policy (as presented)
- Expand the range of analytical tools used to identify and monitor systemic risk (DN) — Priority: Short term
- Explore new instruments capable of addressing time-varying systemic risk, such as limits on LTV and debt service to income (DSTI) ratios (DN, DFSA) — Priority: Short term
- Review the experience with the institutional arrangements, especially the appointment of the government as the designated authority for most macroprudential instruments — Priority: Medium term

Note on timing convention
- Short-term indicates within 18 months; medium-term indicates from 18 months to three years.

### Identification of systemic risk: concepts and scope
- Systemic risks classified into two categories:
  - Structural risk (cross-sectional risk): arises from structural features such as interlinkages between financial intermediaries and institutions that are too important to fail.
  - Cyclical risk: the amount of risk the financial system takes at a point in time relative to its capital and liquidity. Key cyclical risks include credit risk, liquidity risk, and market risk; credit risk is typically the key source of risk in most financial systems.

### Current framework for identifying D-SIFIs (key features and procedures)
- SIFI definition: a bank or mortgage-credit institution (MCI) so large that if it encounters difficulty, this could have far-reaching negative consequences for households, enterprises and the national economy in general.
- SIFI identification criteria (legal thresholds):
  - Size of the balance sheet > 6.5 percent of Denmark’s GDP.
  - Loans comprise more than 5 percent of total sector loans.
  - Deposits comprise more than 5 percent of total sector deposits.
  - To be defined as a SIFI, the institution must exceed one of the limits for two consecutive years.
- Rationale: Measures of interconnectedness were considered, but size and interconnectedness were highly correlated; size criteria were preferred to keep the approach simple and transparent.
- Process and timing:
  - SIFIs are identified every year by the DFSA no later than June 30, based on the most recent financial statements.
  - The first identification took place in June 2014; formal notifications sent on June 19, 2014.
  - New SIFIs must meet the SIFI requirements at the end of the following year (i.e., at least 18 months after having been identified).
  - An institution will cease to be defined as a SIFI if it is below the identification limits for three consecutive years.
  - The MoBG may accelerate enlisting or delisting in cases of important changes (e.g., acquisition, merger, divestment), introducing limited discretion under the law.

### Danish SIFI list and quantitative indicators (2013 consolidated level)
- Institutions meeting quantitative criteria and their indicators:
  - Danske Bank — Total assets in percent of GDP: 160.2; Loans in percent of the total loans of the sector: 30.4; Deposits in percent of the total deposits of the sector: 35.9
  - Nykredit — Total assets in percent of GDP: 76.3; Loans in percent of the total loans of the sector: 32.7; Deposits in percent of the total deposits of the sector: 4.6
  - Nordea Bank Danmark — Total assets in percent of GDP: 44.8; Loans in percent of the total loans of the sector: 16.0; Deposits in percent of the total deposits of the sector: 22.0
  - Jyske Bank — Total assets in percent of GDP: 14.1; Loans in percent of the total loans of the sector: 3.4; Deposits in percent of the total deposits of the sector: 8.9
  - Sydbank — Total assets in percent of GDP: 8.0; Loans in percent of the total loans of the sector: 1.8; Deposits in percent of the total deposits of the sector: 5.4
  - DLR Kredit — Total assets in percent of GDP: 7.9; Loans in percent of the total loans of the sector: 3.5; Deposits in percent of the total deposits of the sector: 0.0
- Note: BRF Kredit previously qualified but is not included in the final list because it merged with Jyske.

*Executive Summary prepared by Prachi Mishra.*

### 8.      The SRC is commissioned to monitor and identify systemic risks in the financial

### _cr14347 - 8.      The SRC is commissioned to monitor and identify systemic risks in the financial

### Monitoring mandate and organizational setup
- The SRC is commissioned to monitor and identify systemic risks in the financial system.
- Monitoring and assessment of systemic risks are conducted in the DN part of the SRC’s secretariat in close corporation with the DFSA.

### Framework for cyclical/time-varying systemic risk
- The framework is based on the European Systemic Risk Board' (ESRB) intermediate targets and related market failures.
- ESRB specifies five intermediate objectives:
  - (1) mitigate and prevent excessive credit growth and leverage;
  - (2) mitigate and prevent excessive maturity mismatch and market illiquidity;
  - (3) limit direct and indirect exposure concentration;
  - (4) limit the systemic impact of misaligned incentives with a view to reducing moral hazard; and
  - (5) strengthen the resilience of financial infrastructures.

### Routine monitoring process and analytical tools
- Broad-based scans for systemic risks are performed on a quarterly basis using a risk dashboard.
- The risk dashboard:
  - Collects relevant indicators connected to intermediate targets of macroprudential policy.
  - Is used to detect signs of market failures or increased risk of market failures being activated when the financial cycle turns.
  - Translates into a short surveillance note containing an assessment of current systemic risks, which is submitted to the SRC.
- Supplemental analytical tools and inputs:
  - Stress tests of the biggest Danish banks conducted by the DN every six months.
  - Event/scenario-analysis (e.g., Black Swan-type analysis).
  - International and national reports (for example from the ESRB) and other available information.
  - For every SRC meeting, a short surveillance note, an updated risk dashboard, and short ad-hoc notes of relevant issues are produced.
- Current limitations:
  - The surveillance framework has been operational for only one year and is under development.
  - For the time being no econometric models or larger statistical frameworks have been developed nor are used in relation to the risk dashboard.

### Possible additional tools: Country Financial Stability Map (Spider-gram)
- Purpose: overarching framework to identify potential sources of macro financial risks in a country (Cervantes et. al, 2014).
- Assesses four broad risks and two conditions:
  - Risks: macroeconomic, inward spillovers, credit, and market and funding liquidity.
  - Conditions: monetary and financial conditions, and risk appetite.
- Each category is represented by an aggregated indicator developed from individual “elements” derived from several macroeconomic and financial indicators.
- Usefulness:
  - Analyzes changes in various dimensions of risk over time.
  - Allows comparison of a country’s evolving risk with the evolution of global risk.

### Findings from Denmark’s Financial Stability Map (2008–2013)
- Market and liquidity risks and inward spillover risks:
  - Declined sharply. Inward spillover risks declined between 2008 and 2010, and have been unchanged since then; market and liquidity risks also declined since 2010.
  - Decline driven by lower risks on both secondary market and bank funding and liquidity.
  - Inward spillover risks declined primarily due to a sharp decline in banks’ foreign assets and an increase in foreign reserves.
- Credit risk and risk appetite:
  - Credit risk rose between 2008 and 2010, reflecting increases in household and corporate debt to GDP, but has been unchanged since then.
  - Risk appetite increased, primarily driven by decreased volatility of stock price and exchange rate movements; and by rising FDI flows.
- Monetary and financial conditions:
  - Tightened slightly between 2008 and 2010, driven by a decline in money supply growth.
- Macroeconomic risks:
  - Remained broadly unchanged.

### Heat maps and financial sector vulnerability
- Heat-map methodology:
  - Creates an overall financial sector vulnerability rating based on an average of different signals—credit cycle, balance sheet soundness, and existence of buffers.
  - Uses thresholds to classify vulnerabilities as “High,” “Medium,” or “Low.”
  - Can be used to analyze changes in risk over time and to create flags or alerts for build-up of systemic risks.
- Empirical conclusion for Denmark:
  - Risks have significantly alleviated compared to pre-crisis times, but some vulnerabilities remain.
  - Heat maps produced for (i) all banks; (ii) commercial banks; and (iii) mortgage banks (see Tables 2, 2a–2c).
  - Although credit indicators were on “high alert” prior to the global financial crisis, more recently they do not indicate specific vulnerabilities.

### Key heat-map indicators and exact figures (selected from Tables 2 / 2a / 2b / 2c)
- Table 2a. Heat Map: All Banks (selected rows; Dec-06 to Dec-13)
  - Deposit/ Loan (FSI definition): 31.5 31.1 29.1 30.1 30.6 31.3 31.2 29.0
  - Deposit/ Loan (authorities' definition): 26.4 30.0 32.7 34.5 33.0 32.8 32.9 33.8
  - FX Liabilities/ Total Liabilities: 25.7 29.4 29.0 26.5 26.2 25.7 22.7 30.8
  - FX Loans/ Total Loans: 22.6 25.7 26.3 25.4 25.7 23.4 21.3 21.2
  - FX Liabilities/ Total Liabilities (excl Euro): 11.6 12.7 13.3 10.9 10.8 9.4 6.7 8.4
  - FX Loans/ Total Loans (excl Euro): 13.2 13.1 13.1 14.0 10.7 8.1 8.3 8.7
  - Capital / Assets: 5.8 6.3 5.5 5.5 5.4 5.1 5.3 7.1
  - Return on Assets: 0.30 0.16 -0.25 -0.08 0.04 -0.02 0.04 0.06
  - Changes in NPLs: -13.5 303.0 106.6 -4.9 14.1 -4.5 6.9
  - Level of NPLs: 0.7 0.6 2.4 4.9 4.7 5.4 5.1 5.5
  - Changes in NPLs (all banks - FSI definition): 101.3 175.0 23.3 -10.1 62.6 -22.4
  - Level of NPLs (all banks -- FSI defintion): 0.6 1.2 3.3 4.1 3.7 6.0 4.0 4.6
- Table 2b. Heat Map: Commercial Banks (selected rows; Dec-06 to Dec-13)
  - Deposit/ Loan (not applicable): 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
  - FX Liabilities/ Total Liabilities: 6.8 9.8 7.9 10.6 11.8 11.9 10.5 13.7
  - FX Loans/ Total Loans: 5.4 8.0 7.9 9.1 9.4 9.4 8.5 7.5
  - Capital / Assets: 4.0 5.7 4.9 3.1 3.0 2.0 2.1 4.7
  - Return on Assets: 0.20 0.11 -0.03 0.02 0.05 0.04 0.05 0.05
  - Changes in NPLs: -15.7 431.3 180.6 19.7 -7.4 2.5 48.5
  - Level of NPLs: 0.1 0.1 0.4 1.0 1.2 1.1 2.1 1.7
- Table 2c. Heat Map: Mortgage Banks (selected rows; Dec-06 to Dec-13)
  - Deposit/ Loan (FSI definition): 74.4 71.2 65.2 73.9 76.1 83.5 86.2 79.9
  - Deposit/ Loan (authorities' definition): 73.4 74.1 79.4 89.4 89.5 87.7 90.9 95.9 105.2
  - Deposit/ Loan (excluding Covered Bonds): 71.4 66.8 77.8 80.7 91.0 96.4 87.3
  - FX Liabilities/ Total Liabilities: 42.4 45.8 46.5 42.5 42.5 41.4 41.0 36.6 47.4
  - FX Loans/ Total Loans: 40.0 42.6 44.0 44.0 44.9 42.0 39.4 40.8
  - Capital / Assets: 7.4 6.8 6.0 7.7 7.8 8.0 8.4 9.2
  - Return on Assets: 0.36 0.19 -0.37 -0.16 0.04 -0.06 0.02 0.07
  - Changes in NPLs: -16.9 211.3 82.2 13.5 -0.7 5.6 4.2
  - Level of NPLs: 1.5 1.2 3.8 7.0 7.9 7.9 8.3 8.7
  - Changes in NPLs (all banks-FSI definition): -58.0
  - Level of NPLs (all banks-FSI definition): 2.4 1.0

### Interpretation of specific vulnerabilities
- Deposit-to-loan ratio:
  - Higher deposit-to-loan ratio indicates lower liquidity risk because deposits are more stable funding.
  - For commercial banks, the deposit-to-loan ratio (FSI definition) is in the high risk range.
  - If loans funded by covered bonds are excluded, the deposit-to-loan ratio is in the medium vulnerability range.
  - Based on the authorities’ definition (includes all loans to and deposits from non-banks, on a consolidated basis), the deposit/loan ratio is now in the low range, after being in the medium range in recent years.
  - Staff view: prudent monitoring should include both individual bank (solo) and group-wide (consolidated) levels; the solo definition should ensure customer deposits exclude deposits from other banks and financial corporations.
- Foreign currency (FX) exposures:
  - For commercial banks in Denmark, both FX loans as well as liabilities exceed the 40 percent threshold (Annex II).
  - FX risk is likely limited because the majority of FX loans are denominated in Euros and the Danish Krone is pegged to the Euro (rows excluding euros show lower shares).
  - Risk may be further mitigated because a large part of Danish FX loans is to subsidiaries and branches abroad, as well as other foreign counterparties.
- Asset quality indicators:
  - Impaired loan ratio (authorities’ definition) has been in the range of medium to high vulnerability.
  - Impaired loan ratio for MCIs increased by 48 percent year-on-year in end 2013, though the level of impaired loans is still very low.
  - 90-day past due NPL ratios (FSI definition) are much lower and have improved over time.
  - This reflects the Danish authorities’ conservative approach to measuring and monitoring asset quality.
- Cross-bank variation:
  - Medium-sized and small banks have higher impaired loan ratios than large banks, and the ratios have increased sharply.
  - Impaired loan ratio for large banks is much lower but has also grown sharply.

### Interconnectedness and systemic risk measures
- Simple interconnectedness measures: interbank loans/total loans, interbank deposits/total deposits, holdings of securities of other institutions.
- SIFI Committee decision:
  - Considered measures of interconnectedness but decided to use size criteria only due to high correlation between interconnectedness and size and to keep approach simple and transparent.
- Econometric/market-based measures discussed:
  - Distress dependence estimated using Segoviano and Goodhart (2009) framework for four D-SIFIs: Danske, Jyske, Sydbank, and Nordea (Nordea using parent bank data).
  - Conditional probabilities of distress estimated for each pair of banks; over 2009–2014 average conditional probabilities of default for other banks given Danske is in distress are slightly higher than conditional probabilities of default for Danske given other banks in stress, with the exception of Nordea.
  - If Nordea goes into default, there is a much higher probability of Danske going to default compared to the reverse.
  - Tail risk measured by joint probability of distress (JPoD) — probability of all four banks becoming distressed.
  - Interconnectedness measured by Banking Stability Index (BSI) — expected number of banks becoming distressed given at least one bank has become distressed.
  - JPoD typically closely follows the average unconditional expected default frequency (EDF) for the banks.

### Systemic importance / Too-Important-To-Fail (TITF) subsidy (Danske example)
- Two approaches used to quantify systemic importance/subsidy for Danske:
  - Contingent Claims Approach (CCA): compares observed CDS spreads and “implied” CDS spreads (disregarding probability of government support).
  - Ratings-based approach: uses rating agencies’ breakdown between stand-alone rating and assessment of government willingness to provide support.
- Findings:
  - Both approaches suggest a positive government subsidy for Danske.
  - Introduction of Bank Package III largely removed the government subsidy for the largest D-SIB.
  - Based on the CCA approach, renewed market turmoil in the Euro Area increased the implicit “too-big-to-fail” subsidy to levels much higher than those seen during the global financial crisis (GFC).
  - Although the trend has reversed since, the subsidy remains large: estimated at 80 bps or equivalent to US$15 billion for Danske Bank.
  - Policy implication: together with intensified supervisory oversight and increased loss absorbency capacity, an effective resolution regime for D-SIBs remains necessary to catalyze the reversal.

### Suggested additional indicators and analyses
- Use additional specific indicators to analyze systemic risk, e.g.:
  - Different components of credit.
  - House prices, both residential and commercial.
- Deeper analyses recommended:
  - NPL ratios by groups of banks (Table 3 provides NPL Ratios by group of commercial banks in percent for 2006–2013).
  - Measures of direct interconnectedness where data permit.

*Source: IMF staff report content unit _cr14347 - 8.*

### 27.      An alternative framework to estimate cross-sector linkages within Denmark is the

### An alternative framework to estimate cross-sector linkages within Denmark is the

### CCA-GVAR framework and scope
- Framework used: Contingent Claims Analysis-Global Vector Auto regression (CCA-GVAR) (Gray et. al 2013).
- Variables modeled: credit spreads for banks, corporate, and sovereign; growth rate of credit; real GDP.
- Sample coverage within Denmark: one bank—Danske (due to data availability), and 111 corporates.
- EL definition: expected loss (EL) ratios as calculated by Moody’s KMV—expected losses to debt holders over a five-year horizon divided by the debt (or the debt default threshold); EL ratios are closely related to “fair value” CDS spreads (“credit spreads” hereafter).

### Evolution of risk indicators, GDP, and credit growth
- EL ratios increased during both the GFC and the euro area turmoil, and have been declining since then.
- ELs are expressed in basis points; real GDP and credit growth are expressed in year-on-year growth rates.
- Notable observation: the banking sector EL ratio spikes when real activity dropped over the 2008–09 period.

### Within-Denmark cross-sector linkages (CCA-GVAR results)
- Feedback effects from other sectors to Danske Bank are strong.
- Examples of estimated responses (reaction of Danske Bank credit spreads to shocks):
  - A 50 basis point shock to sovereign credit spreads increases Danske Bank’s credit spreads by 29 basis points.
  - A 14 basis point shock to corporate spreads increases Danske Bank’s credit spreads by 14 basis points.
  - A one standard deviation shock to GDP increases Danske Bank’s credit spreads by 23 basis points.
- Interpretation:
  - Weak GDP growth affects bank asset quality.
  - The impact of corporate distress on credit dominates, implying credit growth may be more constrained by demand-side rather than supply-side factors.

### Cross-border linkages from Denmark (CCA-GVAR)
- Linkages from Denmark to other countries are mainly to the banking sector, and to credit — especially to the Nordic countries (Norway and Sweden) as well as to other countries.
- Linkages to sovereign and corporate sectors and to GDP in these countries are limited.
- Example quantitative estimate:
  - A one standard deviation shock to the banking sector in Denmark—87 basis points increase in credit spreads—would increase average credit spreads in Norway and Sweden by 19 basis points; and in other countries in the model (excluding Spain, Greece, Italy, Ireland, and Portugal) by 26 basis points.
- Model country coverage: 16 countries (Austria, Belgium, France, Germany, Greece, Ireland, Italy, Netherland, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, and United States).

### Financial network analysis: interconnections and magnitudes
- Method: network analysis using quarterly flow of funds data; maps interlinkages larger than 5 percent of GDP.
- Key sectoral positions (2013Q4, expressed as percent of GDP):
  - Total gross claims on the corporate sector: 442 percent of GDP.
  - Total gross claims on banks: 417 percent of GDP.
  - Net assets highest for households: 143 percent of GDP.
- Cross-border and sectoral asset positions:
  - Other financial intermediaries and insurance and pension funds have significant asset positions abroad (in gross terms).
  - Banks and corporate sector have significant gross asset positions abroad, though not in net terms.
  - Insurance and pension funds play a relatively small role in direct financing of domestic firms but invest indirectly (e.g., mortgage bonds issued by mortgage credit institutions).
- Relative exposures (percent of total assets or liabilities of sector A):
  - Financial claims on the corporate sector exceed 30 percent of total assets for corporate sector itself, financial auxiliaries, general government, and rest of the world (up to 58 percent for the corporate sector itself).
  - Obligations owed to households are owned by insurance corporations and pension funds (85 percent of their liabilities).
  - Largest obligations of households are owned by banks (90 percent of household liabilities); these represent a claim for banks on households (30 percent of bank assets).

### Banking sector centrality and major linkages
- Size of financial sector entities (percent of GDP):
  - Banks: gross financial assets at 422 percent of GDP.
  - Insurance and pension funds: 170 percent of GDP.
  - Other financial intermediaries: 161 percent of GDP.
- Largest financial sector linkages:
  - Interbank linkages: 110 percent of GDP.
  - Linkage between insurance and pension funds and other financial intermediaries: 52 percent of GDP.
- Relative claims on banks by other financial subsectors (as fraction of OFI’s assets):
  - DN: 14 percent.
  - Financial Auxiliaries: 33 percent.
  - Insurance and pension funds: 25 percent.
  - Other financial intermediaries: 23 percent.
- Bank interconnectedness: represents 26 percent of bank assets.

### Policy instruments — existing framework (SIFI capital surcharges)
- SIFI capital surcharges consist of Common Equity Tier 1 (CET1).
- SIFI capital requirement determined by a measure of “systemic importance” and a SIFI scale; capital requirement for SIFIs will constitute 1 to 3 percent of risk-weighted assets.
- Political change: SIFI committee recommended 3.5 percent for the most systemic institution; Parliament reduced the upper limit to 3 percent.
- SIFI scale examples (Systemic importance and corresponding capital requirement in percent):
  - DLR Kredit: Systemic importance 1.9 <=5 → Capital requirement 1
  - Sydbank: 3.2 → (implied range)
  - Jyske Bank: 5.4 → Systemic importance 5–15 → Capital requirement 1.5
  - Nordea Bank Denmark: 16.9 → Systemic importance 15–25 → Capital requirement 2
  - Nykredit Realkredit: 19.7 → (implied range)
  - (25–35) → Capital requirement 2.5
  - Danske Bank: 37.5 → Systemic importance >=35 → Capital requirement 3
- Phasing and aggregate requirements:
  - Capital requirement of SIFIs phased in gradually during 2015–2019.
  - From 2019, a combined capital requirement of at least 11.5–13.5 percent of risk-weighted assets will be required of Danish SIFIs, depending on the institution’s systemic importance.
  - The combined requirement comprises:
    - Pillar I requirement (minimum): 8 percent.
    - Capital conservation buffer: 2.5 percent (applicable to all institutions).
    - Systemic risk buffer: 1–3 percent.
  - Of the total capital requirement of SIFIs, up to 10 percent is stipulated to be comprised of CET1 (excluding the Countercyclical Capital Buffer and Pillar 2 requirements).
- Pillar II requirements:
  - DFSA uses Pillar II requirements depending on risk profile.
  - Current averages: just below an average of 2 percent for SIFIs; more than 3 percent for other banks and mortgage credit institutions.
  - Published institution-level Pillar II requirements (latest available): range from 1.8 percent for Jyske to 2.8 percent for Nordea.
- Crisis management buffer recommendation:
  - SIFI Committee recommended a “crisis management buffer” of 5 percent of risk weighted assets, possibly including certain Tier 1 and Tier 2 instruments (up to 3.5 percent), to be established over a three-year period starting in 2020; decision postponed pending EU Bank Recovery and Resolution Directive implementation.
- Review clause:
  - Final Danish SIFI capital requirements subject to review to be on par with comparable European countries (Sweden, Norway, United Kingdom, Germany, France, the Netherlands, Austria and Switzerland).
  - Current observation: SIFI surcharges are currently lower than other Nordic countries, but DFSA’s publication of individual institutions’ Pillar II requirements improves transparency.

### Policy instruments — Countercyclical Capital Buffer (CCB)
- CCB implementation required under CRDIV; can be set by national authorities to build additional capital buffers in periods of excessive aggregate credit growth.
- CCB specification:
  - Institutions can be ordered to hold up to 2.5 percent of extra CET1 in relation to the basic capital requirement; buffer can be further increased if justified.
- Phasing schedule for CCB:
  - 2015: up to 0.5 percent.
  - 2016: up to 1 percent.
  - 2017: up to 1.5 percent.
  - 2018: up to 2 percent.
  - 2019: up to 2.5 percent.
- Recognition of foreign buffers:
  - Buffer rates set in other countries where Danish institutions have exposure will as a starting point be recognized up to 2.5 percent from 2015.

*Source: IMF Staff Calculations and IMF chapter text.*

### 40.      The operational framework for the CCB (including the calibration) is currently under

### The operational framework for the CCB (including the calibration) is currently under development

### Operational framework for the CCB — activation and calibration
- Preliminary analytical work found that the credit-to-GDP gap (calculated using the one-sided Hodrick-Prescott filter) performed relatively well and is likely to be used as a core indicator for activation of the CCB.
- The credit-to-GDP gap will likely be used to calibrate the buffer based on the BCBS formula.
- Although the credit-to-GDP gap would be one of the primary indicators, authorities plan to use judgment and information available from various indicators of systemic risk.
- When setting the CCB rate, the MoBG will take into account:
  - the deviation of the credit-to-GDP ratio from its long term trend, and
  - other indicators and factors deemed relevant.
- The MoBG’s setting of the buffer rate can be based on a recommendation from the SRC, and it may ask the Danish FSA for input to be used in the buffer decision.
- Design considerations (Annex IV) and BCBS recommendations:
  - Use the credit gap as the core indicator for build-up of systemic risks and for recommending activation of the CCB.
  - Use a BCBS formula to translate the credit gap measure into activation/calibration of the CCB.
  - Use additional contemporaneous indicators for signaling the release phase of CCBs, e.g., growth rate of new loans, market-based measures (credit spreads), and measures of asset quality (NPLs).
  - Include strategies to address domestic and cross-border leakages from use of capital tools.

### Possible additional policy instruments — limitations of the CCB and complementary tools
- Limitations of the CCB:
  - It is a blunt tool, applied uniformly to all exposures and likely to be slow in reacting to build-up of risks in particular credit market segments.
  - It may not be effective where banks hold voluntary buffers above the minimum, or can easily generate capital through strong earnings.
- Complementary instruments:
  - Targeted increases in risk weights for lending to particular segments (e.g., mortgage lending, unsecured consumer credit, corporate lending, or specific segments like commercial property).
  - Sectoral capital requirements or higher provisioning for sectors with higher LTVs or loans exceeding certain LTV thresholds.
  - Legal basis for higher risk weights exists under CRR Articles 124, 164, and 458.
    - Article 124: competent authorities may set higher risk weights of up to 150% on exposures secured by mortgages on immovable property or impose stricter criteria for assessing the mortgage lending value, on the basis of financial stability considerations.
    - Article 164: competent authority may require banks using an IRB approach to apply a higher exposure-weighted LGD floor for retail exposures secured by residential or commercial property than usually allowed under the CRR, on the basis of financial stability considerations.
    - Article 458: allows national authorities, under certain conditions, to impose stricter national requirements to address macroprudential or systemic risks at the national level (tightening own funds, large exposures, public disclosure, liquidity, risk weights for the property sector, or intra financial sector exposures).

### LTV and DSTI caps — uses, transmission channels, and implementation challenges
- Current situation in Denmark:
  - Denmark has LTV limits on mortgage loans funded by covered bonds, but borrowers can supplement by taking other bank loans secured by property not subject to LTV limits.
  - The House Price Bubble Committee (DFSA) has explored options and submitted a report to the MoBG, likely to be submitted to the SRC.
  - Introduction of new instruments like caps on LTV or DSTI would require legislative changes; “softer” requirements could be imposed through supervisory processes (Offsite monitoring tool of the DFSA; “Supervisory Diamond”).
- Transmission channels and comparative features:
  - LTV limits directly reduce funding available to borrowers, screen marginal borrowers, reduce housing demand, decrease house price growth, and restrain credit booms (credit demand channel).
  - DSTI caps enhance borrowers’ resilience to interest rate and income shocks; low DSTI lending is associated with lower delinquency rates and probability of default.
  - LTV caps may become less binding with rising house prices and require successive tightening; DSTI caps can become more binding when house prices and mortgage loans grow faster than disposable income, providing an automatic stabilizer feature.
- Empirical use and cross-country experience:
  - Limits on LTV and DSTI ratios have been used commonly to contain housing-sector vulnerabilities (Figure 9 referenced).
  - Interlocking use of instruments (LTV + DSTI) can improve effectiveness and efficiency; examples include Norway, Sweden, Israel, Hong Kong, and Singapore.
- Implementation challenges for LTV/DSTI:
  - Calibration: setting levels and adjustments during upward/downward phases, identifying targeted loan segments, and types of institutions subject to measures.
  - Application and enforcement: enforcement across financial institutions, phasing-in, operational considerations (announcement and implementation dates), minimizing unintended side-effects (e.g., exceptions for first-time buyers, mortgage insurance).
  - Communication: discussion with financial institutions and explanation to the public, balancing moderation of real estate/credit cycles against negative effects on house buyers and consumers.
- Data and indicators for implementation:
  - Implementing LTV/DSTI should be supported by rich borrower- and loan-specific data (distribution of LTVs and DSTIs across loans, property types, and borrowers).
  - For time-varying instruments or activation, core indicators could include household loan growth and house price growth jointly; additional triggers could include credit indicators by banks and non-banks, balance sheet indicators (average LTV by borrowers across commercial banks and MCIs, LTV distribution across new loans over a period), and affordability indicators (average and distribution of DTIs across new borrowers and all borrowers at a certain point in time).
- Cross-country calibration examples:
  - Malaysia: Central Bank designed an LTV ratio limit of 70 percent on the third and above outstanding housing loan.
  - Brazil: introduced risk weights based on LTV ratios for loans in a specific sector (automobiles); used supervisory data on NPL ratios by vintages and information on LTVs, and applied the Basel II Advanced Approach (IRB) to calibrate risk weights.
  - Norway: FSA guidelines from March 2010 recommended limits on LTV and LTI; cap on LTV lowered to 85 percent in December 2011; changes in risk weights for residential mortgages underway.
  - Sweden: cap of 85 percent applied to all new mortgages or extensions using the home as collateral from 2010; Swedish FSA introduced a risk-weight floor of 15 percent for mortgages in 2013.
  - Other European examples include Netherlands, Poland, and Romania.

### Institutional framework — current setup and roles
- SRC (Systemic Risk Council):
  - SRC was set up by the MoBG in February 2013 following ESRB recommendations.
  - Mandate: identify and monitor systemic financial risks and issue observations, warnings, and recommendations to the DFSA and to the government (if legislative actions are involved). SRC has only an advisory function and no power to give instructions to other authorities.
  - Composition: 10 members from various authorities and external experts:
    - one representative from the MoBG,
    - one from the Ministry of Finance,
    - one from the Ministry of Economic Affairs and the Interior,
    - two from the DFSA,
    - two from DN, and
    - three independent experts.
  - Current members include: the Chairman of the Board of Governors and a Governor from the DN, the Director General and the head of a division from the DFSA, and the three Permanent Secretaries from the government. The Chairman of the DN's Board of Governors chairs the SRC. DN performs secretariat services; DFSA, MoBG, MOF, and the Ministry of Economic Affairs and the Interior participate in the secretariat.
  - Independent experts: must have sufficient knowledge about the financial sector through research or employment in the financial sector and must be independent of institutions covered by the SRC. Current independent experts: a director from the Central Bank of Iceland, former CEO of Nordea Danmark, and a professor from Aarhus University.
  - Appointment and tenure: Minister for Business and Growth appoints members and alternates for up to four years; members may be reappointed. Members are appointed based on recommendations from DN, DFSA, and the two ministries; the Minister can in principle veto recommendations (unlikely in practice). Independent experts are nominated by the Minister based on MoBG staff recommendations and after consultation with DN.
  - Meetings and procedures:
    - SRC meets at least four times a year.
    - Secretariat keeps confidential minutes of meetings containing summaries of important discussions and decisions on observations, warnings, recommendations, and other publications (minutes are confidential internal documents when they contain market-sensitive information).
    - Decisions are taken by majority voting. For recommendations to the government (e.g., on the CCB rate), SRC members from the government abstain; DFSA members must abstain when SRC recommends to the government because DFSA directly advises MoBG outside SRC. SRC is expected to strive for consensus to strengthen recommendations’ effect.
    - High degree of transparency: SRC publishes observations, warnings and recommendations, but may keep some warnings/recommendations confidential for financial stability reasons. SRC issues a press release after each meeting to inform the public.
- Macroprudential authority roles under CRR/CRD IV and Danish law:
  - The MoBG is the national designated macroprudential authority for CRR and CRDIV implementation; under CRDIV each member state appoints a national designated authority and/or competent authority for macroprudential instruments.
  - Responsibility split following Financial Business Act of March 18, 2014 and Bank Package 6:
    - DFSA is the competent authority for Pillar 2 measures and measures under CRR Articles 124 and 164.
      - Pillar 2: complements Pillar 1 to enhance risk management and address risks not (or insufficiently) covered by Pillar 1.
      - Under Article 124, competent authority may set higher risk weights up to 150% on mortgage-secured exposures or impose stricter mortgage lending value criteria for financial stability reasons.
      - Under Article 164, competent authority may require IRB banks to apply a higher exposure-weighted LGD floor for retail exposures secured by property.
    - MoBG is the designated authority for buffers and national flexibility under CRR Article 458.
      - MoBG responsibilities include setting the countercyclical capital buffer, the Systemic Risk Buffer (additional capital requirements for SIFIs), the G-SII-buffer, and higher requirements under Article 458 to address systemic risks (tightening own funds, large exposures, public disclosure, liquidity, risk weights for the property sector, or intra financial sector exposures).

*Source: _cr14347 - 40. The operational framework for the CCB (including the calibration) is currently under development*

### 62.      Despite its prominent role in contributing to financial stability, the DN has no

### _cr14347 - 62.      Despite its prominent role in contributing to financial stability, the DN has no

### Role of Danmarks Nationalbank (DN) in macroprudential policymaking
- DN is an independent institution; one of DN's three main objectives is to contribute to the stability of the financial system.
- DN has no decision making powers on macroprudential instruments—those included in the CRDIV/CRR framework as well as the various buffers.
- Important DN tasks: assessing financial stability and making recommendations on measures that may contribute to enhancing financial stability; recommendations can be independent of SRC decisions.
- DN international participation:
  - The Governor is a voting member of the European Systemic Risk Board (ESRB).
  - The Governor (in addition to the Director General of DFSA) participates in the Nordic Baltic Macroprudential Forum (NBMF).
- DN representation in the SRC:
  - DN holds two of the ten seats in the SRC.
  - The chairman of the DN’s Board of Governors also chairs the SRC.
- Secretariat and agenda role:
  - The Secretariat for the SRC is housed in the DN, which in coordination with DFSA and other agencies prepares a tentative agenda for council meetings.
  - At the beginning of each meeting, the SRC approves the agenda upon a proposal of the chairman.

### Accountability, transparency, and review of the SRC
- MoBG authorization and review:
  - The MoBG is authorized to evaluate the SRC three years after its establishment on the basis of experience with the SRC's function and international developments.
  - The first evaluation will take place in 2016.
- Transparency and “comply or explain” mechanisms:
  - Publication of observations, warnings and recommendations by the SRC and press releases after each meeting.
  - Recipients of a recommendation must either implement the initiative or present a report justifying why the recommendation has not been implemented.
  - If recipient does not follow recommendation, they must publicly explain reasons in accordance with the comply-or-explain principle.
  - The report must be presented to the SRC within three months after the recommendation is notified; in special cases the SRC may decide the report shall be presented earlier.
  - The SRC shall evaluate whether the actions or inactions and the reasons are adequate and publish an assessment of consequences for systemic risks if a public recommendation is not followed.
- Examples of the mechanism in practice:
  - June 2013: SRC issued a recommendation to the government regarding phasing-in of capital requirements legislation in Denmark.
    - Government responded in two stages: first response was a letter published on the SRC website; discussed at third SRC meeting in September 2013 with conclusions published in the press release.
    - Following Parliamentary adoption of the Financial Business act on March 19, 2014, a second follow-up letter from the government was sent to the chair of the SRC and published on the SRC website; discussed at the fifth SRC meeting in March 2014; an overall assessment of the government’s follow-up was published in the subsequent press release.
- Political limits to accountability:
  - MoBG may comply with SRC recommendations, but recommendations may not win parliamentary support; final legislation can differ from SRC recommendations.
  - Example: SRC recommended full implementation of CCB as from January 1, 2015; MoBG complied but parliamentary process approved phased-in implementation from 2015 to 2019.
  - Once legislation delegates decision making power (e.g., to the MoBG for deciding the CCB rate), accountability lies with the MoBG and is less subject to parliamentary constraints.
- Assessment and outlook:
  - Authorities note macroprudential arrangement is off to a good start but must be more extensively tested.
  - DN has publicly expressed disagreement with MoBG having ultimate decision making power over macroprudential policy (e.g., in the September quarterly review).
  - All agencies and an independent expert member agreed SRC is functioning well, system is very transparent, and the “comply or explain” rule makes it accountable.
  - Staff view: system should be reviewed after more experience is gained; a review of the SRC is planned for 2016.
  - Near-term priority: ensure coordination among agencies is working adequately and keep independent experts in the SRC appraised on developments.

### Interaction with the ESRB and bottom-up risk identification
- ESRB mandate and methods:
  - ESRB mandated to identify and prioritize systemic risks at the European level.
  - ESRB uses top-down risk surveillance and assessment and a complementary “bottom-up” risk identification and assessment at a quarterly frequency.
  - ESRB sends bottom-up questionnaires (BUQ) to all Advisory Technical Committee members individually to gather views on existing and new risks.
  - BUQ complements material such as ECB top-down surveillance, ESRB Risk Dashboard, Secretariat’s Issues Note, thematic notes, semi-annual Analysis of National Banking Systems, and market intelligence reports by the ECB and the Bank of England.
  - Bottom-up approach suits identification of early-stage risks, regionally focused risks, differing perspectives on existing risks, monitoring structural risks, and cross-checking the top-down approach.
- Denmark’s responses:
  - Separate answers to the BUQ are provided by the DN and the DFSA.

### Cross-country models for macroprudential policymaking
- Three prevalent models:
  - Model 1: Macroprudential mandate assigned to the central bank; decisions made by its Board (examples: Czech Republic, New Zealand).
  - Model 2: Mandate assigned to a dedicated committee within the central bank structure (examples: United Kingdom, Malaysia).
  - Model 3: Mandate assigned to a committee outside the central bank, with central bank participating on the committee (examples: Australia, France, United States).
- Denmark’s framework:
  - Denmark’s institutional framework is perhaps closest—though not identical—to Model 3.
  - Model 3 can accommodate a desire for a strong role of the ministry (finance/business).
  - Few countries (e.g., Norway and Switzerland) have similar frameworks where ultimate macroprudential regulatory powers are with the government.
    - Norway: Ministry of Finance has authority to set the counter cyclical buffer (CCB) and risk weights on residential mortgages; prudential supervisor sets limits on LTVs for mortgages.
    - Switzerland: Government has decision-making power, upon recommendation by the SNB, which must consult FINMA (the regulator).
- Risks and mitigants:
  - Dominant government role risks delaying action and compromising independence of participating agencies (Nier and others, 2011).
  - Ministry participation can be useful when legislative changes are needed to expand toolkit or perimeter.
  - Risks can be countered by sound governance, transparency, and clear accountability; some countries deter risks by assigning central bank the chairmanship (Australia), a strong voice (Mexico), or a veto (Germany).
- IMF view:
  - Desirable for the central bank to play an important role in macroprudential policy (IMF, 2011a; Nier and others, 2011; IMF, 2013a; Viñals, 2011).
  - Arguments: central bank expertise in systemic risk identification; alignment of incentives; improved coordination between macroprudential and monetary policy while preserving independence; shielding policymaking from political interference.
  - ESRB recommendation aligns: member states recommended to “ensure that the central bank plays a leading role in the macroprudential policy and that macroprudential policy does not undermine its independence in accordance with Article 130 of the Treaty.”

### Assessment of institutional arrangements and possible adjustments
- DN and DFSA role enhancement:
  - Staff discussed whether DN and/or DFSA role could be further enhanced; changes to decision making powers would require legislation in Parliament.
  - Options discussed: give DFSA or DN decision making authority for a new instrument—would increase their role but require coordination with other agencies (e.g., MoBG, designated authority for the CCB).
- Recommended near-term actions:
  - Review SRC in 2016 as planned.
  - In run-up to review, SRC could discuss institutional arrangements’ progress and recommend to government any needed changes in authority for new or existing instruments.
  - Priority to ensure coordination among agencies is adequate and keep independent experts appraised.

### Country Financial Stability Map: indicators and methodology (selected points)
- Indicator categories and variables (excerpted):
  - Macroeconomic risks: Output gap (percent); Inflation rate (percent y/y); Unemployment rate (percent); Budget balance to GDP; Public debt to GDP; Current account balance to GDP; Domestic credit from banks (percentage deviation from the trend); House prices (national currency).
  - Inward spillover risks: Exports to GDP; Gross foreign assets of banking sector to GDP; LIBOR-OIS spread--Euro Area (bps); Implied volatility--United States (percent); Gross international reserves to short-term external debt; FX market pressure index.
  - Credit risks: Growth in domestic credit from banks (percent y/y); Corporate debt to GDP; Return on assets (annualized, percent) - corporates; Household debt to GDP; House price growth (percent y/y).
  - Market and liquidity risks: Currency bid-ask spread (bps); Stock market turnover (annual average, times); Liquid assets to short-term liabilities; Foreign liabilities of banking sector to GDP.
  - Monetary and financial conditions: Short-term real interest rate (percent); Growth of real broad money (percent y/y); Gross portfolio inflows to GDP; Gross FDI inflows to GDP.
- Methodology summary:
  - A z-score is computed for each selected variable and normalized between 0-10 (rank 10 if the 99th percentile, and five corresponds to the long-term average).
  - Sub-indicator scores: equally weighted average of rankings assigned to each variable.
  - Element scores: equally weighted average of associated sub-indicator rankings.
  - Aggregated risk indicator: equally weighted average of associated elements.
  - Further detail referenced to pages 13–15 in http://www.imf.org/external/pubs/ft/wp/2014/wp1499.pdf (note: citation present in source).

### Financial sector vulnerability indicators and thresholds (excerpt)
- Credit Cycle sub-indicator thresholds (excerpt):
  - Credit-to-GDP (x) / Credit-to-GDP ‘gap’ (y):
    - High: x > 5 percent OR y > 1.5 s.d. AND x >= 10 percent
    - Medium: 3 < x <= 5 percent
    - Low: x <= 3 percent
  - % of FX assets (x):
    - High: x > 40 percent
    - Medium: 25 <= x <= 40 percent
    - Low: x < 25 percent
  - Deposit-to-loan ratio (x):
    - High: x <= 85 percent
    - Medium: 85 < x <= 100 percent
    - Low: x > 100 percent
  - Leverage:
    - High: x <= 3 percent
    - Medium: 3 < x <= 7 percent
    - Low: x > 7 percent
  - Asset quality [Level of NPL (x), Change in NPL (y)]:
    - High: x in top 10th percentile of pooled distribution OR y > 20 percent
    - Medium: 0 <= y <= 20 percent
    - Low: y < 0 percent
  - Profitability [ROE (x), ROA (y)]: high vulnerability if x OR y < 0

### Appendix III — Implicit government subsidy for Too Important to Fail (TITF) banks: Danske
- Two approaches used to measure implicit government subsidy for Danske (based on IMF (2014) methodology):
  1. Contingent Claims Approach (CCA):
     - Compares observed CDS spreads with fair value (“implied”) CDS spreads calculated based on equity price information.
     - Observed CDS spreads reflect both probability of bank default and likelihood/size of government support; fair value CDS disregards government support.
     - CCA estimates indicate observed CDS spreads are lower than fair value spreads, implying a positive subsidy.
     - Latest data available: subsidy amounts to 80 bps, which is equivalent to US$15 billion.
     - Historical peak: 86 bps (equivalent to US$17bn) around the Lehman crisis; declined thereafter before rising around end-2011 to levels much higher than the global financial crisis; began declining again in 2013 but currently at levels comparable to the peak around the GFC.
  2. Ratings-based approach:
     - Uses rating agencies’ breakdown between stand-alone rating and assessment of government willingness to provide support.
     - Estimation steps:
       1. Calculate ratings boost from government support via regression of ratings’ uplift on banks’ fundamentals and government capacity across a wide sample.
       2. Convert ratings boost into a funding cost spread using historical estimates of the relationship between credit ratings and bond spreads from Sousa (2000).
       3. Multiply funding cost spread by total liability of Danske to get implicit subsidy in US dollar.
     - Ratings-based results:
       - In 2012, subsidy amounted to US$4.8 bn.
       - Peak of 37 bps in 2009 (equivalent to US$6.8 bn) before starting to decline.
       - Although estimated subsidy may be about 17 bps in the current scenario, in the event Danske goes into distress (rating just below investment grade) the subsidy can increase up to 76 bps.
     - Conclusion: ratings-based estimates are somewhat lower in magnitude than CCA but broadly consistent qualitatively; implicit subsidies have declined from crisis peaks but remain high and can increase substantially in crisis scenarios.

*Italic: Content based only on the supplied IMF source text.*

### Appendix IV. Countercyclical Capital Requirements:

### Appendix IV. Countercyclical Capital Requirements: Guidelines

### Framework and legal/design features
- The CCB should follow the recommendations of the Basel Committee on Banking Supervision (BCBS).
- The CCB should be determined at national level for all exposures to counterparties in that country.
- Banks have to meet the CCB with common equity tier 1 or they will be subject to restrictions on dividend distributions.
- The framework depends on national regulator’s discretion but contains international reciprocity to make the CCB more effective and to ensure the level playing field between domestic and foreign banks operating in more than one jurisdiction.

### Core indicator and rationale
- The credit gap should be used as a core indicator for assessing the build-up of systemic risks and recommending the activation of the CCB.
- Studies suggest that among potential variables (credit growth, GDP growth, property prices, banks’ profitability), the credit gap is the single most powerful indicator of banking crises, including for emerging market economies.
- The CCB should be activated when credit growth is judged to be excessive and associated with an increase in systemic risks; in particular, activation should be considered if the credit-to-GDP ratio exceeds its trend value by a certain magnitude.

### Calculation of the credit gap
- Calculate the credit-to-GDP ratio using a broad measure of credit to the private sector, comprising all lending by domestic and foreign financial institutions as well as debt raised in financial markets, to avoid underestimating risks.
- Total credit to the domestic non-financial sector is available from the BIS.
- To estimate the gap, extract a trend from the ratio using the Hodrick-Prescott filter with relatively high smoothing parameters: lamda equal to 400,000 instead of 1600 for quarterly data.
- Note: estimates of the credit gap are highly sensitive to the sample, the value of lambda, and the credit series used.

### Use of multiple indicators and judgment
- All available information should be used to analyze systemic risks when making recommendations on activation of the CCB.
- Instead of relying mechanically on the credit gap, Staff should use a range of indicators and analyze their joint behavior; combined information generally provides a better signal than a single indicator.

Core indicators
- Credit-to-GDP gap

Additional indicators
- Change in credit/GDP ratio (m-o-m and y-o-y change)
- Credit growth (m-o-m and y-o-y change)
- Debt service ratio
- Asset price growth (m-o-m and y-o-y change), gaps and levels of house prices-to-income, real commercial property prices
- Leverage on individual loans or at the asset level (e.g. loan-to-value (LTV) ratio—an average and a distribution across new loans over a period and existing loans at a given point in time, margin requirements)
- Decomposition between core and non-core liabilities and the wholesale funding ratio (gap and level)
- Current account deficits

### Calibration: mapping credit gap to CCB size
- When using the credit gap to calibrate the CCB, the BCBS formula should be used to translate the credit gap measure into the buffer reference guide.
- The credit gap serves as a common starting point in guiding decisions on buffer rates.
- A lower threshold value of the credit gap defines the level at which the buffer should be considered to be deployed:
  - If the indicator is below the lower threshold, the buffer guide is zero.
  - If the indicator is above the upper threshold the buffer guide should be set at its maximum which under the BCBS proposal should be 2.5 percent of risk-weighted assets.
  - The CCB varies linearly between the lower and upper threshold.
- The values of 2 percent and 10 percentage points for the lower and upper threshold are found to provide a reasonable and robust specification based on historical banking crises across countries (but depend on the smoothing parameter).
- The BCBS methodology based on these common thresholds performs well for a large majority of countries.

### Activation and deactivation: indicators and process
- Deactivation strategies depend on how financial system stress materializes. If systemic risks dissipate and financial imbalances unwind, the CCB should be reduced gradually based on the same set of indicators used for activation.
- The same indicators may not capture both build-up and release phases because:
  - Build-up phase requires leading indicator properties.
  - Release phase requires contemporaneous indicators of banking distress.
- A prompt release of the CCB will be necessary to lessen the risk of a credit crunch due to regulatory capital requirements.

Indicators useful for signaling the beginning of the release phase (possibly in combination)
- Growth rate of new loans
- High-frequency market-based indicators that are forward looking like credit spreads, price-based measures of default or distress or “near-coincident” indicators of systemic stress
- Asset quality

### Addressing leakage and cross-border issues
- Domestic leakages can occur via increased connected lending by nonbank entities or via off-balance sheet vehicles; these need to be addressed by expanding the perimeter of capital requirements and/or consolidating such activity.
- Cross-border leakages from capital tools can be addressed by subsidiarization and reciprocity arrangements.

*Source: Appendix IV. Countercyclical Capital Requirements (excerpt) — IMF.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2014/_cr14347.pdf_