Prudential definition of assets: micro and macro prudential perspective



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Prudential definition of assets: micro and macro prudential perspective Santiago de Chile November 2015 Presented by Salome Skhirtladze Authors: Giorgi Kadagidze, Otar Nadaraia, Salome Skhirtladze, Vakhtang Sikharulishvili, Ana Kvaratskhelia

Contents 1 Prudential definition of assets: Current challenges 2 Financial ratios: Micro foundation 3 Financial ratios: Macro foundation 4 Financial ratios: Asset classification system 5 Areas for further research & Conclusion

Prudential definition of assets: Current challenges 1 No uniform practice of segregating assets into risk buckets 2 3 Absence of common objective criteria indicating borrowers financial health, while general qualitative criteria promote different interpretations Most widely used quantitative criteria past due days (NPL >90 days); extensive restructuring practice can mask real creditworthiness; 4 Accounting perspective (IAS 39): ability for interpretation of Objective evidence of impairment: too late, too little

If asset classification system can capture financial strength of borrower, forbearance loses its relevance

Prudential definition of assets: Current challenges Can the financial ratios explain vast majority of risks? Liquidity Leverage Activity Profitability

Financial ratios: Micro foundation Credit risk assessment entails complex analyses of financial and business risks, however empirical evidence shows that synthetic ratings can predict corporate distress with high accuracy rate: Sveriges Riskbank (2013) National Bank of Czech Republic (2011) 90% 3 financial ratios <1 y prediction 7 financial Ratios 70%-90% 5 financial ratios 88% 9 financial ratios Altman Z-Score (1968) Ohlson (1980)

Financial ratios: Micro foundation Financial ratios have a prominent role in complex credit risk models, such as big3 rating agencies 6< 5.5< 5< 5-6 4.5-5.5 4-5 4-5 3.5-4.5 3-4 3-4 2.5-3.5 2-3 2-3 1.75-2.5 1.5-2 <2.00 Low Business Risk Debt/EBITDA <1.75 Medium Business Risk <1.5 High Business Risk 7,00 6,00 5,00 4,00 3,00 2,00 1,00-18,00 16,00 14,00 12,00 10,00 8,00 6,00 4,00 2,00-15< 10-15 6-10 3-6 14< 9-14 5-9 2.75-5 13< 7-13 4-7 2.5-4 2-3 1.75-2.75 1.5-2.5 <2 <1.75 <1.5 High Business Risk EBITDA/Interest Thresholds of Leverage and coverage ratios by credit risk buckets, S&P Medium Business Risk Low Business Risk Minimal Modest Intermediate Significant Aggressive Highly Leveraged

Financial ratios: Micro Prudential framework US leveraged lending guidance (2013) incorporates financial ratios into asset classification: Leveraged loan: Total Debt-to-EBITDA > 4X criticized' or 'special mention loan: Debt-to-EBITDA > 6x Risk Sensitivity Simplicity BASEL capital framework (revisions to the standardized approach for the credit risk): Senior corporate exposures: Revenue (firm size) and debt/equity (leverage) Exposures secured by residential real estate: LTV (Loan-to-value) and DSR (debt service ratio)

Financial ratios: Macro foundation Increased focus on micro data in macro prudential oversight and analyses. What are the advantages of Micro data? Macro measures (DTI/Credit to GDP) may mask debt service burden distribution across borrowers; Micro data can provide early warning signals, since it captures changes in distribution of credit risks across sectors and industries; Facilitates meaningful comparison across countries (low versus high IR environment); and financial stability reports

Financial ratios: Macro foundation DSR distribution: Canada vs US Distribution of DSR was similar in 2001; In 2004, the household sector in Canada was less vulnerable to macro economic shocks than US Shifts in the shape of US DSR can be explained by increasing risk taking in mortgage lending;

Financial ratios: Macro foundation Still there are no common standards or approaches to interpret this data Interpretations of corporate ratios vary among Corporate Interest Coverage Ratios (% of debt) Below 1 1 to 2 2 to 3 Above 3 EBIT/Interest Expense 11 12 13 11 12 13 11 12 13 11 12 13 11 12 13 Germany France Italy Spain Portugal 100% 80% 60% 40% 20% 0% different publications of IMF (ICR set either at < 1 or <2); Considering low IR environment, does interest only servicing capacity suffice low risk? When risks identified, mitigating factors such as NPL, reserves (IFRS or regulatory) and capital buffers are not discussed;

Incorporation of financial ratios into asset classification system: NBG approach Financial Ratios Adjustments Corporate 1. Leverage: Debt to EBITDA and Debt to Equity 2. Liquidity 3. Coverage: Interest Coverage Ratio Retail 1. Leverage: Loan to Value or Debt to Income 2. Coverage: Payment to Income Mild Stress Scenarios Firm Size Industry IR FX un-hedged Borrower Maturity Income Level Group Corporate Corporate & Retail Retail

Incorporation of financial ratios into asset classification system: NBG approach Addition to Asset Classification System: National Bank of Georgia Ratios by Sector Other Factors considered: SME 20% stricter IR - Mild FX - Mild Maturity Ability for restructuring Risk Sector Debt/ EBITDA EBIT/Interes t Expenses Real Estate Development 2.50 3.50 Auto dealers 2.75 3.25 Construction Companies (non-developers) 2.50 3.25 Hotels and Tourism 3.00 3.00 Restaurants 3.00 3.00 Service 3.00 3.00 Production and Trade of Clothes, Shoes and Textiles 3.25 2.75 Pharmacy 3.25 2.75 Telecommunication 3.00 2.75 Energy 3.50 2.50 Other Production 2.75 3.25 Other, including scrap metals 2.75 3.25

Incorporation of financial ratios into asset classification system: NBG aproach IFRS Provisioning (before collateral discount) 70% 60% 50% 40% 30% 20% 10% QIS The study is performed based not on historical data, but rather on the testing of current classification of exposures, using synthetic rating approach. The initial results are promising. 0% 0 1 2 3 4 5 6 7 8 9 10 Interest Coverage Ratio Source: NBG calculation based on a sample of corporate borrowers, 2012

Incorporation of financial ratios into asset classification system: NBG aproach IFRS Provisioning (before collateral discount) 70% 60% 50% 40% 30% 20% 10% QIS The study is performed based not on historical data, but rather on the testing of current classification of exposures, using synthetic rating approach. The initial results are promising. 0% 0 1 2 3 4 5 6 7 8 9 10 Interest Coverage Ratio Source: NBG calculation based on a sample of corporate borrowers, 2012

Incorporation of financial ratios into asset classification system Advantages 1 Comparability, risk sensitivity and simplicity 2 Limited possibility to misinterpret credit risk; reduced reliance on banks estimates; Forbearance Mitigated 3 Limited possibility to misinterpret impairment triggers under IAS 39 4 Timely supervisory attention once the ratios are deteriorated 5 Powerful tool for preventing macro systemic imbalances bottom up approach

Incorporation of financial ratios into asset classification system Advantages Credit risk disclosures are vital for understanding the institution-specific risk profile and relevant credit risk mitigation techniques for managing these risks. 1 Portfolio distribution by ratios will boost general market understanding about the risks inherent in portfolios; enhanced market discipline 2 3 It will facilitate meaningful comparison of risk profiles among institutions and countries The banks will provide explanations on the role of financial ratios in credit risk management

Areas for further research Predictability QIS Cyclicality 1. Micro (borrower) level; 2. Macro Level ratios versus conventional macro measures*; 1. Statistical analyses based on historical data; 2. Expert analyses testing current exposures; 1. Mild versus severe stress scenarios; 2. Address via provision versus capital charges; *Macro level analyses: it is important to analyze financial ratios with regard to country-specific factors, such as the level of economic development, average interest rates, term structure, country risk and volatility in earnings across economies

Draft Paper Can be Found: https://www.nbg.gov.ge/uploads/publications/on/paper_incorporation_of_financial_ratio s_into_prudential_definition_of_assets_micro_and_macro_prudential_perspective.pdf

In 2014 ECB initiated asset quality review among largest EU Banks Among others, the NPL adjustments amounted to 140 billion EUR based on simplified criteria: Past due 90 days Impaired Under IFRS/GAAP Forbearance Unlikely to pay general criteria Can the incorporation of financial ratios into asset classification system provide permanent solution to underestimated credit risks? Will it enhance our understanding on real credit risk inherent in banks loan portfolios? Financial ratios?

Slovenia Case Overall debt leverage of the Slovenian corporate sector, measured by debt-to-ebitda From 2004, the corporate sector leverage more than doubled; Major investments: into overheated construction industry; In 2012, about 46% of corporate debt had debt/ebitda above 10x. Source: EBRD, 2014