Modern Risk Modern Risk Modern Risk Management Modern Risk - PowerPoint PPT Presentation

Interest rate risk Interest rate risk • Since the price of a bond fluctuates with market interest rates, the risk that an investor faces is that the price of a bond held in a portfolio will decline if market f b d h ld f l ll d l f k interest rates rise. 11 d • This risk, which is a form of market risk, is referred to Thi i k hi h i f f k i k i f d nd Chinabon ovember 20 as interest rate risk and is the major risk faced by erence investors in the bond market investors in the bond market. EFFAS ‐ EBC an Confe eneva, 2 nd N • Bond’s price sensitivity to changes in market interest rates (i.e., a bond s interest rate risk) depends on rates (i e a bond’s interest rate risk) depends on E G – various features of the issue, such as maturity, coupon rate, and embedded options , p – Current term structure of interest rates. EFFAS ‐ EBC and Chinabond Seminar 15 Geneva, 2nd November 2011

Term structure of interest rates Term structure of interest rates Term structure of interest rates can be described in several ways: 1. 1 yield curve yield curve ‐ the relationship between (zero coupon) yield and the relationship between (zero coupon) yield and maturity. Forward curve ‐ (instantaneous) forward rate as a function of ( ) 2. 11 d nd Chinabon ovember 20 maturity 3. Discount rate as a function of maturity erence EFFAS ‐ EBC an Confe eneva, 2 nd N • The important point here is that portfolios have different exposures to how the yield curve shifts. y E G The corresponding risk exposure is sometimes called yield curve • risk. The implication is that any measure of interest rate risk that assumes that the interest rates changes by an equal number of assumes that the interest rates changes by an equal number of basis points for all maturities (referred to as a ‘‘parallel yield curve shift’’) is only an approximation. EFFAS ‐ EBC and Chinabond Seminar 16 Geneva, 2nd November 2011

Reinvestment risk Reinvestment risk • Reinvestment risk is the risk that the proceeds received from the payment of interest and principal (i.e., scheduled payments, called proceeds and principal prepayments) that are available for proceeds, and principal prepayments) that are available for reinvestment must be reinvested at a lower interest rate than the security that generated the proceeds. 11 d • For amortizing securities (i.e., securities that repay principal F i i i i (i i i h i i l nd Chinabon ovember 20 periodically),reinvestment risk is greater than for plain vanilla fixed erence income. Reinvestment risk, in particular, is present when an EFFAS ‐ EBC an Confe eneva, 2 nd N investor purchases a callable or principal prepayable bond. Zero ‐ coupon bonds eliminate reinvestment risk up to maturity time. • Reinvestment risk is related to the volatility of the forward rates Reinvestment risk is related to the volatility of the forward rates E G with corresponding maturities and can therefore be regarded as a sot of interest rate risk. EFFAS ‐ EBC and Chinabond Seminar 17 Geneva, 2nd November 2011

The Impact of Embedded Options The Impact of Embedded Options • a bond may include a provision that allows the issuer to retire, or call, all or part of the issue before the maturity date. From the investor’s perspective there are disadvantages to call provisions: investor s perspective, there are disadvantages to call provisions: 1. The cash flow pattern of a callable bond is not known with certainty because it is not known when the bond will be called. 11 d 2. 2 B Because the issuer is likely to call the bonds when interest rates have h i i lik l ll h b d h i h nd Chinabon ovember 20 declined below the bond’s coupon rate, the investor is exposed to erence reinvestment risk, i.e., the investor will have to reinvest the proceeds when the bond is called at interest rates lower than the bond’s h th b d i ll d t i t t t l th th b d’ EFFAS ‐ EBC an Confe eneva, 2 nd N coupon rate or yield to maturity. • Because of these disadvantages faced by the investor, a callable E G bond is said to expose the investor to call risk . The same disadvantages apply to mortgage ‐ backed and asset ‐ backed securities where the borrower can prepay principal. p p y p p • The embedded option value is sensitive to the volatility of the security, so that finally it is related to the specific interest rate risk EFFAS ‐ EBC and Chinabond Seminar 18 Geneva, 2nd November 2011

Liquidity risk Liquidity risk Liquidity risk can materialize in two basic forms: • Market liquidity risk which is the risk that a firm Market liquidity risk , which is the risk that a firm will not be able to sell an asset quickly without materially affecting its price; materially affecting its price; 11 d nd Chinabon ovember 20 • Funding liquidity risk , which is the risk that a firm erence will not be able to meet expected cash flow will not be able to meet expected cash flow EFFAS ‐ EBC an Confe eneva, 2 nd N requirements (future and current) by raising funds on short notice funds on short notice. E G The two types of liquidity risks can interact with each other and through markets affect multiple each other and, through markets, affect multiple institutions. EFFAS ‐ EBC and Chinabond Seminar 19 Geneva, 2nd November 2011

Systemic liquidity shortfalls Systemic liquidity shortfalls • In periods of rising uncertainty, the interaction can give rise to systemic liquidity shortfalls. A negative spiral between market and funding liquidity can develop whereby a sudden lack of funding funding liquidity can develop whereby a sudden lack of funding leads to multiple institutions attempting to sell their assets simultaneously to generate cash. 11 d • These correlated fire sales of assets may lead suppliers of liquidity Th l d fi l f l d li f li idi nd Chinabon ovember 20 to insist on higher margin and larger haircuts (the deduction in the erence asset’s value used as collateral) as the value of collateral(assets EFFAS ‐ EBC an Confe eneva, 2 nd N pledged) declines. Creditors may become even less likely to provide funding, fearing insolvency of their counterparties, resulting in significant funding disruptions. g g p E G This self ‐ reinforcing process can lead to downward cascades in • asset prices and to further declines in a firm’s net worth, morphing into a systemic crisis as many institutions become affected into a systemic crisis as many institutions become affected. EFFAS ‐ EBC and Chinabond Seminar 20 Geneva, 2nd November 2011

Liq idit risk management frame ork Liquidity risk management framework • A bank should establish a robust liquidity risk management framework that ensures it maintains g sufficient liquidity, including a cushion of unencumbered, high quality liquid assets , to g q y q 11 d nd Chinabon ovember 20 withstand a range of stress events, including those erence involving the loss or impairment of both unsecured and EFFAS ‐ EBC an Confe eneva, 2 nd N secured funding sources. • A bank should define a liquidity risk tolerance that q y E G should ensure that the firm manages its liquidity strongly in normal times in such a way that it is able to g y y withstand a prolonged period of stress. EFFAS ‐ EBC and Chinabond Seminar 21 Geneva, 2nd November 2011

Credit risk (counterparty risk) ( p y ) definitions Narrow sense definition Credit risk is a possibility of investor's loss arising from a borrower who • does not make payments as promised. Such an event is called a default. does not make payments as promised Such an event is called a default This risk should be preferably called default risk . Wide sense definition 11 d Credit risk is the risk that changing credit quality of a counterparty will C dit i k i th i k th t h i dit lit f t t ill • nd Chinabon ovember 20 affect the value of a bank’s positions .The credit quality of a counterparty erence refers generally to the counterparty’s ability to perform on that obligation. This encompasses both the counterparty’s default probability and This encompasses both the counterparty’s default probability and EFFAS ‐ EBC an Confe eneva, 2 nd N anticipated recovery rate. Default occurs when a counterparty is unwilling or unable to fulfill its contractual obligations. This is the extreme case. E • C Credit risk arises only if the position is an asset, i.e. when it exhibits a dit i k i l if th iti i t i h it hibit G positive replacement value. If a counterparty defaults, the loss can be the position’s total market value or, a percentage of that value (called loss given default) The percentage of total market value that be recovered is given default). The percentage of total market value that be recovered is called recovery rate. EFFAS ‐ EBC and Chinabond Seminar 22 Geneva, 2nd November 2011

Market vs. credit risk direct measurement • Market risk exposure arises from unexpected security price fluctuations. Using long histories of daily price fluctuations we can distinguish between “typical” and fl d h b “ l” d “atypical” trading days in order to assess either 11 expected losses (on a typical day) or unexpected losses expected losses (on a typical day) or unexpected losses d nd Chinabon ovember 20 (on an atypical day that occurs with a given likelihood). erence • Credit events such as default or rating downgrades are • Credit events such as default or rating downgrades are EFFAS ‐ EBC an Confe eneva, 2 nd N rare, often nonrecurring events. Thus, we do not have enough statistical power to estimate directly daily g p y y E G measures of credit risk exposure. It is however possible to measure it in indirect way using market data, and within framework of credit risk models. i hi f k f di i k d l EFFAS ‐ EBC and Chinabond Seminar 23 Geneva, 2nd November 2011

External ratings External ratings “A bank should be aware that external ratings are a useful starting point for credit analysis but are no useful starting point for credit analysis, but are no substitute for full and proper understanding of the 11 d underlying risk, especially where ratings for certain d l i i k i ll h ti f t i nd Chinabon ovember 20 asset classes have a short history or have been erence EFFAS ‐ EBC an Confe eneva, 2 nd N shown to be volatile” • Enhancements to the Basel II framework 2009 Enhancements to the Basel II framework 2009 E G EFFAS ‐ EBC and Chinabond Seminar 24 Geneva, 2nd November 2011

Credit risk concentrations Credit risk concentrations The typical situations in which risk concentrations can arise include: exposures to a single counterparty, borrower or group of connected • counterparties or borrowers; counterparties or borrowers; • industry or economic sectors, including exposures to both regulated and nonregulated financial institutions such as hedge funds and private equity 11 d firms; firms; nd Chinabon ovember 20 • geographical regions; erence • exposures arising from credit risk mitigation techniques, including EFFAS ‐ EBC an Confe exposure to similar collateral types or to a single or closely related credit l ll l l l l l eneva, 2 nd N protection provider; • trading exposures/market risk; g p E G • exposures to counterparties (eg hedge funds and hedge counterparties) through the execution or processing of transactions (either product or service); ); • off ‐ balance sheet exposures, including guarantees, liquidity lines and other commitments. EFFAS ‐ EBC and Chinabond Seminar 25 Geneva, 2nd November 2011

3 RECENT CHANGES IN REGULATION ENVIRONMENT ENVIRONMENT EFFAS ‐ EBC and Chinabond Seminar 26 Geneva, 2nd November 2011

Why it is important to study Basel 2, 2.5 and 3 Wh it i i t t t t d B l 2 2 5 d 3 • Recommendations Set by the Basel Committee on Banking Supervision, are based on the best practice of g p , p risk management in the form of generalised rules, taking into account consultations with leading banks. g g 11 d nd Chinabon ovember 20 • It creates an international standard which for erence regulators to formulate capital adequacy and liquidity regulators to formulate capital adequacy and liquidity EFFAS ‐ EBC an Confe eneva, 2 nd N requirements for financial institutions in order to avoid falling in a vortex of financial risk. g E G • A Basel 2, 2.5 and 3 in its advanced form ‐ relying on internal models ‐ is therefore a benchmark for internal models is therefore a benchmark for implementing the best practices in risk management. EFFAS ‐ EBC and Chinabond Seminar 27 Geneva, 2nd November 2011

Revisions to the Basel II Market Risk 2009 (Basle 2.5) • The Proposed Rule is a modification of the existing risk ‐ based capital treatment of market risk, of the Market Risk Amendment of 1996 (MRA) 1996 (MRA). Changes to the trading book rules are warranted because of • changes in the markets and the large trading book losses banks 11 d suffered in 2007 and 2008. For example, the existing rule does not ff d i 2007 d 2008 F l h i i l d nd Chinabon ovember 20 adequately capture the credit risk of positions held in banks' erence trading books . Among other changes, the Proposed Rule ensures EFFAS ‐ EBC an Confe eneva, 2 nd N that capital is held against these positions by applying credit risk capital charges to trading positions. • the Proposed Rule introduces several new capital requirements the Proposed Rule introduces several new capital requirements, E G including stressed ‐ value ‐ at ‐ risk (SVaR), the incremental risk charge , and charges for correlation trading positions. EFFAS ‐ EBC and Chinabond Seminar 28 Geneva, 2nd November 2011

Incremental Risk Charge Incremental Risk Charge • Banks have included certain types of positions in the market risk capital framework that contain significant levels of credit risk. This was not envisioned when the MRA was first implemented. To was not envisioned when the MRA was first implemented To address this situation, the a new capital requirement is established, the incremental risk charge. Incremental risk is the default and 11 d credit migration risk that is not reflected in a bank's VaR based credit migration risk that is not reflected in a bank s VaR ‐ based nd Chinabon ovember 20 measures . erence “After the crisis manifestation of 2007 and 2008 Basel Committee • EFFAS ‐ EBC an Confe eneva, 2 nd N decided in 2009 to expand the scope of the capital charge. The decision was taken in light of the recent credit market turmoil where a number of major banking organisations have experienced j g g p E G large losses, most of which were sustained in banks’ trading books. Most of those losses were not captured in the 99%/10 ‐ day VaR.” BIS Consultative Paper “Guidelines for Computing Capital for BIS Consultative Paper Guidelines for Computing Capital for Incremental Risk in the Trading Book” July 2008 EFFAS ‐ EBC and Chinabond Seminar 29 Geneva, 2nd November 2011

Incremental risk in the trading book Incremental risk in the trading book • Since the losses have not arisen from actual defaults but rather from credit migrations combined with widening of credit spreads from credit migrations combined with widening of credit spreads and the loss of liquidity, applying an incremental risk charge covering default risk only would not appear adequate . For 11 d example, a number of global financial institutions commented that l b f l b l fi i l i i i d h nd Chinabon ovember 20 singling out just default risk was inconsistent with their internal erence practices and could be potentially burdensome EFFAS ‐ EBC an Confe eneva, 2 nd N • The incremental risk capital requirement must be consistent with a one ‐ year horizon and a 99.9 percent confidence level, the measurement standard under the credit risk capital framework measurement standard under the credit risk capital framework. E G This capital requirement would include losses arising from defaults and credit migrations in covered positions subject to specific interest rate risk interest rate risk. EFFAS ‐ EBC and Chinabond Seminar 30 Geneva, 2nd November 2011

Trading and covered positions Trading and covered positions • A trading position is defined as a position that is held by the bank for the purpose of short ‐ term resale or with the intent of benefiting from actual or expected short ‐ term i t t f b fiti f t l t d h t t price movements, or to lock in arbitrage profits. • Covered position definition includes trading assets and • Covered position definition includes trading assets and 11 d nd Chinabon ovember 20 trading liabilities that hedge covered positions. In addition, erence the trading asset or trading liability must be free of any EFFAS ‐ EBC an Confe eneva, 2 nd N restrictive covenants on its tradability or the bank must be able to hedge its material risk elements in a two ‐ way market A trading asset or trading liability that hedges a market. A trading asset or trading liability that hedges a E G trading position is a covered position only if the hedge is within the scope of the bank's hedging strategy. EFFAS ‐ EBC and Chinabond Seminar 31 Geneva, 2nd November 2011

Liquidity risk management q y g importance • Liquidity reserve vs. capital reserve: when Bear Stearns defaulted in 2008, its capital reserve where above the minimal regulatory capital required by Basel II, but was not available (liquid) for meeting margin calls. , ( q ) g g • Liquidity problems are typically low frequency but potentially high impact events, and the board of directors and senior management of a bank may pay more attention to other, higher frequency risks or may limit a bank s pay more attention to other, higher frequency risks or may limit a bank’s 11 d nd Chinabon ovember 20 liquidity risk mitigation due to competitive considerations. In addition, an expectation that central banks will provide liquidity erence • support alongside the guarantees to depositors provided by deposit support, alongside the guarantees to depositors provided by deposit EFFAS ‐ EBC an Confe eneva, 2 nd N insurance, could diminish the incentives of the bank to manage its liquidity as conservatively as it should. This is typical moral hazard situation (in which a party insulated This is typical moral hazard situation (in which a party insulated • • E G from risk behaves differently from how it would behave if it were fully exposed to the risk) increases the responsibility of supervisors to ensure that a bank does not lower its standard of liquidity risk management and that a bank does not lower its standard of liquidity risk management and adopt a less robust liquidity risk management framework as a result. EFFAS ‐ EBC and Chinabond Seminar 32 Geneva, 2nd November 2011

Liquidity issues for the interaction q y between market and credit risk an excerpt from “ Findings on the interaction an excerpt from Findings on the interaction of market and credit risk”, Basel Committee on Banking Supervision Working Paper No 16 2009 Banking Supervision, Working Paper No. 16, 2009 11 d nd Chinabon ovember 20 erence • “Liquidity conditions interact with market risk and credit “Li idit diti i t t ith k t i k d dit EFFAS ‐ EBC an Confe eneva, 2 nd N risk through the horizon over which assets can be liquidated. liquidated E G • In particular, deteriorating market liquidity often forces banks to lengthen the horizon over which they can banks to lengthen the horizon over which they can execute their risk management strategies. EFFAS ‐ EBC and Chinabond Seminar 33 Geneva, 2nd November 2011

Liquidity issues: continuation… Liquidity issues continuation • As this time horizon lengthens, overall risk exposures generally increase, as does the contribution of credit risk relative to market risk. The liquidity of traded k l k k h l d f d d products can vary substantially over time and in 11 unpredictable ways. Such liquidity fluctuations, all else unpredictable ways Such liquidity fluctuations all else d nd Chinabon ovember 20 equal, should have a larger impact on prices of erence products with greater credit risk. products with greater credit risk. EFFAS ‐ EBC an Confe eneva, 2 nd N • Liquidity risks are not accounted for in pricing models used in trading on the financial markets . Since all g E G models are not geared towards this scenario, all participants in an illiquid market using such models will f face systemic risks”. i i k ” EFFAS ‐ EBC and Chinabond Seminar 34 Geneva, 2nd November 2011

Taking into account European g p specificities • In July 2011 European Commission issued a proposal containing two parts: a directive governing the access to deposit ‐ taking activities and a regulation governing how activities of credit activities and a regulation governing how activities of credit institutions and investment firms are carried out • The proposal EU regulation is faithful to Basel's spirit, letter and p p g p 11 d nd Chinabon ovember 20 level of ambition. But it is not an easy exercise to apply rules to 8.200 banks amounting for 53% of global assets. erence • • It is necessary to take into account the specificities of the It is necessary to take into account the specificities of the EFFAS ‐ EBC an Confe eneva, 2 nd N European banking sector, with its mutual or cooperative banks (13% of the European banking sector) and its bank and E i insurance groups. G • Gradual development is needed: not to destabilise the financing of the European economy The new prudential rules will of the European economy. The new prudential rules will represent a considerable effort since our banks will have to find some 460 billion euros of additional capital. EFFAS ‐ EBC and Chinabond Seminar 35 Geneva, 2nd November 2011

Positi e side of implementation in EU Positive side of implementation in EU • the effort will take place over period of time from 2013 to 2019 • it will be accompanied and compensated by an increased level of trust (lacking today) 11 d nd Chinabon ovember 20 • there is an estimate of the implementation impact by modelling: the probability of severe systemic crises erence should decrease by 70%. h ld d b 70% EFFAS ‐ EBC an Confe eneva, 2 nd N • moreover, if a crisis nevertheless will occur, it will be less serio s less serious. E G • the Basel committee predicts that the EU's GDP will increase by 0 3 to 2 percentage points per year once increase by 0.3 to 2 percentage points per year, once all measures are fully implemented. EFFAS ‐ EBC and Chinabond Seminar 36 Geneva, 2nd November 2011

Role of credit rating agencies: g g European point of view • A hot topic, which directly concerns European banks and which is tackled in the proposal: the role of credit rating agencies. Excerpt from Michel Barnier member of the European Commission Excerpt from Michel Barnier, member of the European Commission responsible for Internal Market and Services, speech: 11 d “We are too dependent on credit rating agencies. As a result, I wish to “W t d d t dit ti i A lt I i h t nd Chinabon ovember 20 suppress as much as possible the reference to credit ratings in the erence prudential rules . This is essential for financial stability. EFFAS ‐ EBC an Confe Today, we propose to strengthen the requirement for the banks to lead h h f h b k l eneva, 2 nd N their own risk analyses, without relying mechanically on credit rating agencies”. E G These proposals will be followed by a new legislative initiative aiming at • improving the framework for credit rating agencies, in particular regarding p g g g , p g g their activity on sovereign debt. EFFAS ‐ EBC and Chinabond Seminar 37 Geneva, 2nd November 2011

Proposal content Proposal content The Regulation contains the detailed prudential requirements for credit institutions and investment firms and it covers: 1. capital : The Commission’s proposal increases the amount of own funds banks need to hold as well as the quality of those funds. It q y 11 d nd Chinabon ovember 20 also harmonises the deductions from own funds in order to determine the amount of regulatory capital that is prudent to erence recognise for regulatory purposes. recognise for regulatory purposes. EFFAS ‐ EBC an Confe eneva, 2 nd N 2. liquidity : To improve short ‐ term resilience of the liquidity risk profile of financial institutions, the Commission proposes the introduction of a Liquidity Coverage Ratio (LCR) the exact introduction of a Liquidity Coverage Ratio (LCR) ‐ the exact E G composition and calibration of which will be determined after an observation and review period in 2015. EFFAS ‐ EBC and Chinabond Seminar 38 Geneva, 2nd November 2011

Proposal content, continuation Proposal content continuation 3. leverage ratio : In order to limit an excessive build ‐ up of leverage on credit institutions' and investment firms' balance sheets, the Commission also proposes that a leverage ratio be subject to Commission also proposes that a leverage ratio be subject to supervisory review. Implications of a leverage ratio will be closely monitored prior to its possible move to a binding requirement on 11 d 1 January 2018 1 January 2018. nd Chinabon ovember 20 4. counter party credit risk : consistent with the Commission's policy erence vis ‐ à ‐ vis OTC (over the counter) derivatives (IP/10/1125), changes EFFAS ‐ EBC an Confe eneva, 2 nd N are made to encourage banks to clear OTC derivatives on CCPs (central counterparties). 5. 5 single rule book : the financial crisis highlighted the danger of single rule book : the financial crisis highlighted the danger of E G divergent national rules. A single market needs a single rule book. The Regulation is directly applicable without the need for national transposition and accordingly eliminates one source of such transposition and accordingly eliminates one source of such divergence. The Regulation also sets a single set of capital rules., EFFAS ‐ EBC and Chinabond Seminar 39 Geneva, 2nd November 2011

4 GLOBAL FINANCIAL STABILITY AND SYSTEMIC RISKS AND SYSTEMIC RISKS EFFAS ‐ EBC and Chinabond Seminar 40 Geneva, 2nd November 2011

Problem: “Risk ‐ sensitive” regulation g failed to stop the crisis? • “If the bad apple theory were correct, financial crises would be “If th b d l th t fi i l i ld b random, arising whenever there was a sufficient concentration of evil ‐ doers But crashes are not random; they always follow booms evil doers. But crashes are not random; they always follow booms. 11 d nd Chinabon ovember 20 And booms are not caused by people doing things they know are erence risky, but by people doing things they perceive as safe ; so safe as y y p p g g y p EFFAS ‐ EBC an Confe eneva, 2 nd N to justify doubling up and betting the house. This is the essential challenge of banking regulation, a challenge ill • E G served by the “Basel II” approach of requiring the banks to put aside capital depending on their perception of risks. So ‐ called “risk ‐ sensitive” regulation adds fire to the boom and ice to the bust”. i i ” l i dd fi h b d i h b ” Prof Avinash D. Persaud EFFAS ‐ EBC and Chinabond Seminar 41 Geneva, 2nd November 2011

Global Financial Stability Report 2009: y p when risk become systemic The GFSR 2009 feature methodologies that can shed light on when direct and indirect financial linkages can become systemic. Specifically, the d i di t fi i l li k b t i S ifi ll th authors present complementary approaches to assess financial sector systemic linkages, including: 11 d • The network approach, which tracks the reverberation of a credit event h k h h h k h b f d nd Chinabon ovember 20 and a liquidity squeeze throughout the system. 
 erence • The co ‐ risk model, which exploits market data to assess systemic linkages EFFAS ‐ EBC an Confe eneva, 2 nd N at an institutional level and is an important method of assessing the markets’ perception of how much more tightly the fortunes of financial institutions are linked together during stress times. 
 E G • The default intensity model, which measures the probability of failures of a large fraction of financial institutions (default clustering) as a result of both direct and indirect systemic linkages. EFFAS ‐ EBC and Chinabond Seminar 42 Geneva, 2nd November 2011

Russian interbank market liquidity q y (Buzdalin, Smirnov et al, 2005) • It was a part of the work done in 2005 for Deposit Insurance Agency. We were using the data on the number and volume of the inter bank lending of the Russian banks in the first quarter 2005. inter ‐ bank lending of the Russian banks in the first quarter 2005 Since only about 250 Russian banks are active on the inter ‐ bank • lending market, the suggested algorithm is suitable only for these 11 d banks, whereas the available statistic data is insufficient for b k h h il bl i i d i i ffi i f nd Chinabon ovember 20 identification of clusters for other banks. However, the 250 banks erence active on the inter ‐ bank lending market account for 90% of the total EFFAS ‐ EBC an Confe eneva, 2 nd N assets of the banking system. • Based on the computations performed, 18 main clusters were identified (see next slide ) The hierarchical structures within the identified (see next slide ). The hierarchical structures within the E G banking system are represented by arrows that indicate the banks of the senior clusters that redistribute liquidity to the subordinate EFFAS ‐ EBC and Chinabond Seminar 43 Geneva, 2nd November 2011

Russian interbank market: identified clusters, 2005 Urals ib-Nikoil et al Proms vyazbank, BIN Bank, Interregional Inves tment Bank Avangard et al. CORE: Banksof Samara Sberbank, Region, Foreign Banks Vnes htorgbank, Soyuz 11 иностранным d Vnes heconombank nd Chinabon ovember 20 Interprombank et Foreign Banks иностранным al erence Indus trial and banking groups Ga p o ba Gazprombank, , EFFAS ‐ EBC an Confe eneva, 2 nd N Indus trial and Cons truction Bank, Alfa-Bank, MDM Bank, Bank of Khanty-Mans iys k Satellite Satellite Satellite Satellite Banks Banks Banks Banks E G Autonomous Groups Nomos Nomos -Bank -Bank Metallinves Metallinves t t Lefco-Bank et Lefco-Bank et et al Bank et al al Orgbank et al Vozrozhdeniye Bank, Bank Zenit et al EFFAS ‐ EBC and Chinabond Seminar 44 Geneva, 2nd November 2011

Brasilian interbank network (Cont & Bastos 2009) 11 d nd Chinabon ovember 20 erence EFFAS ‐ EBC an Confe eneva, 2 nd N E G EFFAS ‐ EBC and Chinabond Seminar 45 Geneva, 2nd November 2011

The Empirically Constructed CDS Network p y for US Banks and Outside Entity (Markose et al, 2010) 11 d nd Chinabon ovember 20 erence EFFAS ‐ EBC an Confe eneva, 2 nd N E G EFFAS ‐ EBC and Chinabond Seminar 46 Geneva, 2nd November 2011

Global Financial Stability Report, y p , April 2010 The GFSR report examines systemic risk and the The GFSR report examines systemic risk and the redesign of financial regulation. In particular: 11 d nd Chinabon ovember 20 • implementing Systemic ‐ Risk ‐ Based Capital erence Surcharges ; Surcharges EFFAS ‐ EBC an Confe eneva, 2 nd N • the role of central counterparties in making over ‐ E the ‐ counter derivatives safer; h d i i f G • the effects of the expansion of global liquidity on receiving economies. EFFAS ‐ EBC and Chinabond Seminar 47 Geneva, 2nd November 2011

Global Financial Stability Report, y p , October 2010 • In this GFSR, it was noted that improvements in market infrastructure could help mitigate systemic liquidity risks. k • For instance, some risks associated with collateral 11 d management in secured funding markets could be i d f di k ld b nd Chinabon ovember 20 addressed through greater use of central erence counterparties for repurchase agreements and counterparties for repurchase agreements and EFFAS ‐ EBC an Confe eneva, 2 nd N through ‐ the ‐ cycle haircuts, or minimum haircut requirements, for collateral. q , E G • Also, nonbank financial institutions that contribute to systemic liquidity risk should receive more oversight y q y g and regulation. EFFAS ‐ EBC and Chinabond Seminar 48 Geneva, 2nd November 2011

Global Financial Stability Report, y p , April 2011 • Broadly speaking, at their core the Basel III rules are microprudential, aimed at encouraging banks to hold higher liquidity buffers and to lower maturity mismatches to lower the liquidity buffers and to lower maturity mismatches to lower the likelihood that any individual institution will run into liquidity problems. They are not intended or designed to mitigate systemic 11 d liquidity risks where the interactions of financial institutions can liquidity risks, where the interactions of financial institutions can nd Chinabon ovember 20 result in the simultaneous inability of institutions to access erence sufficient market liquidity and funding liquidity under stress. EFFAS ‐ EBC an Confe eneva, 2 nd N • The document suggests three separate methods of measuring systemic liquidity risk, each of which could be used to construct a macroprudential tool. Each technique measures an institution’s p q E G ongoing contribution to system ‐ wide liquidity risk, thereby establishing an objective basis on which to charge an institution for the externality it imposes on the financial system. the externality it imposes on the financial system. EFFAS ‐ EBC and Chinabond Seminar 49 Geneva, 2nd November 2011

September 2011 GFSR : Sovereign p g Vulnerabilities and Contagion Risks • Sovereign balance sheets remain fragile in a number of advanced economies despite steps toward fiscal consolidation. The lack of sufficient political support for lid ti Th l k f ffi i t liti l t f medium ‐ term fiscal adjustment and growth ‐ enhancing reforms worsens funding pressures for sovereigns amidst a reforms worsens funding pressures for sovereigns amidst a 11 d nd Chinabon ovember 20 softer growth outlook. These pressures increase the risk that the debt dynamics of vulnerable sovereigns will slide erence into a spiral of deterioration in the absence of a coherent i t i l f d t i ti i th b f h t EFFAS ‐ EBC an Confe eneva, 2 nd N policy framework and adequate backstops to prevent the spread of contagion. spread of contagion. E G • The spillover of sovereign risks to the banking sector has put funding strains on many banks operating in the euro area and depressed their market capitalization. EFFAS ‐ EBC and Chinabond Seminar 50 Geneva, 2nd November 2011

Nouriel Roubini point of view Nouriel Roubini point of view about the next (wave) of crisis about the next (wave) of crisis • February 2, 2011, www.spiegel.de 11 d ...I don't expect that my views are going to be implemented during I d 't t th t i i t b i l t d d i nd Chinabon ovember 20 this crisis. We might have to wait until the next one, until more erence radical proposals will be considered. My worry is that if we don't EFFAS ‐ EBC an Confe eneva, 2 nd N create a system where these crises occur less frequently, then the backlash we have seen in recent times against market oriented economies, against reforms, against globalization, against free , g , g g , g E G trade, could become more severe the next time around. The lesson is actually if another crisis were to occur down the line, it's going to be even more virulent then the last one even more it s going to be even more virulent then the last one, even more damaging and costly for any measure you want to look at, income, jobs, wealth, fiscal costs. We just can not afford that.... EFFAS ‐ EBC and Chinabond Seminar 51 Geneva, 2nd November 2011

Joseph Stiglitz on ‘Ersatz Capitalism’ p g p and Moral Bankruptcy • Joseph Stiglitz is a recipient of the Nobel Memorial Prize in Economic Sciences (2001). In 2010 he calls “ersatz capitalism” the version of capitalism in the US ended up with is a flawed, unfair system that socializes economic losses and privatizes the gains . i i h i • “‘An awful lot of people are not managing their own money. In old ‐ style 19th Century capitalism, I owned my company, I made a mistake, I bore the 11 d consequences consequences… Today, (at) most of the big companies you have managers who, Today (at) most of the big companies you have managers who nd Chinabon ovember 20 when things go well, walk off with a lot of money. When things go bad the shareholders bear the costs.” erence • As Stiglitz sees it, the current economic paradigm is a symptom of a deeper, As Stiglitz sees it the current economic paradigm is a symptom of a deeper EFFAS ‐ EBC an Confe eneva, 2 nd N society ‐ wide problem . • “We have created a society in which materialism overwhelms moral commitment, in which the rapid growth that we have achieved is not sustainable p g E G environmentally or socially, in which we do not act together to address our common needs. Market fundamentalism has eroded any sense of community and has led to rampant exploitation of unwary and unprotected individuals. There has been an erosion of trust — and not just in our financial institutions. It is not too b i f t t d t j t i fi i l i tit ti It i t t late to close these fissures.” EFFAS ‐ EBC and Chinabond Seminar 52 Geneva, 2nd November 2011

5 TRADITIONAL CREDIT ANALYSIS: EXPERT JUDGEMENT EXPERT JUDGEMENT EFFAS ‐ EBC and Chinabond Seminar 53 Geneva, 2nd November 2011

Flexibility of y expert judgement systems • The key feature of expert ‐ judgement systems is flexibility. The prevalence of judgmental rating systems reflects the view that the determinants of default are too complicated to be captured by a single quantitative p p y g q model . The quality of management is often cited as an example of a risk determinant that is difficult to assess through a quantitative model. • In order to foster internal consistency, banks employing expert judgment In order to foster internal consistency, banks employing expert judgment 11 d nd Chinabon ovember 20 rating systems typically provide narrative guidelines that set out ratings criteria. However, the expert must decide how narrative guidelines apply erence to a given set of circumstances. g EFFAS ‐ EBC an Confe eneva, 2 nd N • The flexibility possible in the assignment of judgmental ratings has implications for the types of ratings review that are feasible. As part of the ratings validation process, banks will attempt to confirm that raters follow ratings validation process, banks will attempt to confirm that raters follow E G bank policy. However, two individuals exercising judgment can use the same information to support different ratings. Thus, the review of an expert judgment rating system will require an expert who can identify the p j g g y q p y impact of policy and the impact of judgment on a rating. EFFAS ‐ EBC and Chinabond Seminar 54 Geneva, 2nd November 2011

Expert Systems p y of assessing credit quality Historically, bankers have relied on the “5 C’s of credit” principles of professional judgment to assess credit principles of professional judgment to assess credit quality: 11 d 1. Capacity nd Chinabon ovember 20 erence 2. Character 2. Character EFFAS ‐ EBC an Confe eneva, 2 nd N 3. Collateral E G 4. Covenants 5. Conditions 5. Conditions EFFAS ‐ EBC and Chinabond Seminar 55 Geneva, 2nd November 2011

Capacity Capacity Capacity: The most critical • How exactly do the borrower(s) intend to repay • How exactly do the borrower(s) intend to repay the loan ? The lender considers cash flow (based 11 d on the 3 year profit and loss projections) as th 3 fit d l j ti ) nd Chinabon ovember 20 compared to similar or the same businesses. The erence EFFAS ‐ EBC an Confe b borrower(s) previous payment history is a critical ( ) h l eneva, 2 nd N factor in the lenders decision to make the loan. E G • Do the borrower(s) have any secondary sources to repay the loan if the business is not able to to repay the loan if the business is not able to repay the loan? EFFAS ‐ EBC and Chinabond Seminar 56 Geneva, 2nd November 2011

Capacity analysis Capacity analysis • Traditional financial ratios to evaluate the ability of an issuer to meet its obligations including profitability ratios, debt and coverage ratios d bt d ti • Cash flow analysis is of the most important role. By analyzing these individual statement of cash flows, creditors can these individual statement of cash flows creditors can 11 d nd Chinabon ovember 20 examine such aspects of the business as: erence – The source of financing for business operations, whether g p EFFAS ‐ EBC an Confe eneva, 2 nd N through internally generated funds or external sources of funds. – The ability of the company to meet debt obligations (interest and principal payments) and principal payments). E G – The ability of the company to finance expansion through cash flow from its operating activities. – The ability of the company to pay dividends to shareholders. – The flexibility the business has in financing its operations. EFFAS ‐ EBC and Chinabond Seminar 57 Geneva, 2nd November 2011

Character Character Character: the foundation of sound credit • The lenders impression of the borrower(s), subjective p ( ), j determination of trustworthiness to repay the loan as agreed. 11 d nd Chinabon ovember 20 • Quality of management, business qualifications and skills erence EFFAS ‐ EBC an Confe eneva, 2 nd N • Corporate Governance, including risk management • Integrity E G – Consistency of actions, values, methods, measures, principles, expectations, and outcomes. – ethical reputation, the honesty, truthfulness, accuracy of hi l i h h hf l f actions EFFAS ‐ EBC and Chinabond Seminar 58 Geneva, 2nd November 2011

Collateral Collateral Collateral: reducing credit risk exposure • Considered not only in the traditional sense of assets pledged to secure the debt their value in a liquidation sale if the business secure the debt, their value in a liquidation sale if the business cannot repay the loan, but also to the quality and value of those unpledged assets controlled by the issuer. 11 d nd Chinabon ovember 20 • Collateral provides a lender with an alternative source to repay the loan if the business is not successful. Other than cash, the lender erence must make a guess at the value of most collateral. must make a guess at the value of most collateral. EFFAS ‐ EBC an Confe eneva, 2 nd N Common types of collateral include: accounts receivable, inventory, • machinery and equipment, real estate, marketable securities (traded stocks/bonds) cash and guarantees that may be (traded stocks/bonds), cash, and guarantees that may be E G collateralized (if the guarantor pledge assets to back part or all of the guaranty). EFFAS ‐ EBC and Chinabond Seminar 59 Geneva, 2nd November 2011

Covenants Covenants Covenants (vs. Indentures) have value impact, influence the risk to creditors. They help p , y p prevent the transfer of wealth from debt holders to equity holders. 11 d nd Chinabon ovember 20 • An indenture is a formal debt agreement that erence establishes the terms of a bond issue, while , EFFAS ‐ EBC an Confe eneva, 2 nd N covenants are the clauses of such an agreement. • Covenants specify the rights of bondholders and Covenants specify the rights of bondholders and E G the duties of issuers, such as actions that the issuer is obligated to perform or is prohibited issuer is obligated to perform or is prohibited from performing. EFFAS ‐ EBC and Chinabond Seminar 60 Geneva, 2nd November 2011

Conditions Conditions • Conditions: general economic environment for the particular type of business both nationally and locally p yp y y 11 • What conditions outside of the control of the owners • What conditions outside of the control of the owners d nd Chinabon ovember 20 or managers could negatively impact this business? erence • Local competition, industry trends, general economic L l titi i d t t d l i EFFAS ‐ EBC an Confe eneva, 2 nd N conditions, legal and regulatory restrictions, and liability concerns liability concerns. E G • Some conditions are outside of the borrower’s control e.g. industry trends and general economic conditions – i d d d l i di i but they may affect the business’ ability to succeed. EFFAS ‐ EBC and Chinabond Seminar 61 Geneva, 2nd November 2011

6 CREDIT RISK MODELS EFFAS ‐ EBC and Chinabond Seminar 62 Geneva, 2nd November 2011

Ordinal vs Cardinal scale Ordinal vs Cardinal scale • Risk assessment methods based on scoring methods that rate the level of risk factors on an ordinal scale are widely used, especially in expert systems expert systems The use of verbal scales for eliciting estimates of risk’s severity and • probabilities, is subject to some persistent human errors when 11 d assessing risks. The fact that simple scoring methods are easy to i i k Th f h i l i h d nd Chinabon ovember 20 use, combined with the difficulty and time delay in tracking results erence with respect to reality, means that the proliferation of such EFFAS ‐ EBC an Confe eneva, 2 nd N methods may well be due entirely to their perceived benefits • The need for portfolio analysis is one of the strong reasons why risk assessment approaches should describe risk in terms of cardinal assessment approaches should describe risk in terms of cardinal E G scale (PD, LGD, correlations, etc), to achieve the necessary flexibility of risk description. Mapping from ordinal to cardinal scale is not always an easy exercise always an easy exercise. EFFAS ‐ EBC and Chinabond Seminar 63 Geneva, 2nd November 2011

Market Based Credit Risk Models Market Based Credit Risk Models • For publicly traded company , market models can be used to derive probabilities of default from the market p prices of corporate debt and equity. The general disadvantage of these models is that they rely on the g y y 11 d nd Chinabon ovember 20 availability of market data and also on market erence efficiency (in particular, liquidity of the traded EFFAS ‐ EBC an Confe eneva, 2 nd N instruments). In the lending industry, however, most entities are either unlisted or thinly traded on the stock E G exchange, which restricts the use of such models. • Market based models can be further categorized into g structural models and reduced form models EFFAS ‐ EBC and Chinabond Seminar 64 Geneva, 2nd November 2011

Structural models Structural models • Structural models link the default of an entity to the value of the firm through its equity price . These models treat equity as an option to buy the company’s assets, and use it ti t b th ’ t d option pricing formulae to link the equity price, which is used as a proxy of the (generally unobservable) firm s asset used as a proxy of the (generally unobservable) firm’s asset 11 d nd Chinabon ovember 20 value, to likelihood of default. erence • The obvious benefit of such models is that they can use the EFFAS ‐ EBC an Confe eneva, 2 nd N latest market prices to provide a “marked to market” likelihood of default for individual companies. • The major shortfall of structural models is that they Th j h tf ll f t t l d l i th t th E G deliberately simplify the capital structure of a firm, meaning that these models are hardly suitable for analyzing meaning that these models are hardly suitable for analyzing assets that have unusual capital structures or unusual pay ‐ offs. EFFAS ‐ EBC and Chinabond Seminar 65 Geneva, 2nd November 2011

Reduced form models Reduced form models • Reduced form models are generally used in areas such as bond and credit derivative pricing , and rather than producing likelihood of default measures, reduced ‐ form d i lik lih d f d f lt d d f models are generally used to calculate prices of such assets, or spreads between the assets’ yields and the reference or spreads between the assets yields and the reference 11 d nd Chinabon ovember 20 risk ‐ free yield. Probability of Default (PD) can then be derived from these spreads, if some explicit assumptions erence about Loss Given Default (LGD) are admitted (for example, b t L Gi D f lt (LGD) d itt d (f l EFFAS ‐ EBC an Confe eneva, 2 nd N constant LGD) . • The reduced ‐ form models assume that the prices of such • The reduced ‐ form models assume that the prices of such E G assets follow stochastic processes. Thus, there are two sets of difficulties: firstly the correct process description has to be developed, and secondly the process needs calibrating to market data. EFFAS ‐ EBC and Chinabond Seminar 66 Geneva, 2nd November 2011

Latest research Latest research • The latest academic thinking in the credit risk modeling area is that the debt and equity market g q y data can be combined to produce hybrid models that allow for a more precise estimation of 11 d nd Chinabon probabilities of default (PD) and possibly of loss ovember 20 given default (LGD). erence EFFAS ‐ EBC an Confe eneva, 2 nd N • Detailed discussion of the credit risk models is present in our complementary material (Credit p p y ( E G Risk Modeling: Literature Review), as well as the problem of measuring PD, LGD and correlations of defaults. EFFAS ‐ EBC and Chinabond Seminar 67 Geneva, 2nd November 2011

CreditMetrics model CreditMetrics model • CreditMetrics is one of the first proprietary models of credit risk. It utilizes external credit rating as a main credit risk driver (weak side of the model assumptions) . d i ( k id f th d l ti ) • That is, the CreditMetrics model is built around a credit migration or transition matrix that measures the probability migration or transition matrix that measures the probability 11 d nd Chinabon ovember 20 that the credit rating of any given debt security will change erence over the course of the credit horizon. The process of rating EFFAS ‐ EBC an Confe eneva, 2 nd N migration is therefore regarded as a Markov chain. • Empirical transition matrices are published by S&P (please see “Default, Transition, and Recovery: 2010 Annual Global “D f lt T iti d R 2010 A l Gl b l E G Corporate Default Study And Rating Transitions”) EFFAS ‐ EBC and Chinabond Seminar 68 Geneva, 2nd November 2011

Credit ratings and historic default g frequencies • two ways of deriving PD s from independent credit ratings are used in practice: cohort analysis and duration analysis. • • Cohort analysis is the simplest method to estimate default Cohort analysis is the simplest method to estimate default probabilities when credit ratings are available for a relatively large cross ‐ section of firms or loans. For a given observation period, the 11 d probability of migrating from one credit rating to another is simply b bili f i i f di i h i i l nd Chinabon ovember 20 the observed proportion of firms that experience such migration. In erence particular, cohort analysis can be used to estimate the default EFFAS ‐ EBC an Confe eneva, 2 nd N probability given the credit rating of the firm or bond at the beginning of the period. • Duration analysis accounts for the time spent in different credit Duration analysis accounts for the time spent in different credit E G ratings during the observation period. In duration analysis, the migration intensity is determined as the proportion of firm ‐ years that migrated from one rating category to the other divided by the that migrated from one rating category to the other divided by the total number of firm ‐ years. EFFAS ‐ EBC and Chinabond Seminar 69 Geneva, 2nd November 2011

Econometric models Econometric models • Regression analysis of macro ‐ and/or microeconomic time series a kind of statistical credit scoring method. Macroeconomic ‐ based models are motivated by the M i b d d l ti t d b th observation that default rates in the financial, corporate, and household sectors increase during recessions. and household sectors increase during recessions. 11 d nd Chinabon ovember 20 • Regressions based on microeconomic data are more erence suitable for credit risk analysis. iI particular, widely used in EFFAS ‐ EBC an Confe eneva, 2 nd N practice are models based on accounting reporting and default data, aggregated as financial indicators and ratios that fall into broad categories like liquidity; capital that fall into broad categories like liquidity; capital E G adequacy, etc. • Hybrid econometric models combine macroeconomic Hybrid econometric models combine macroeconomic values, credit ratings, market variables and financial ratios to produce more accurate estimates of default probabilities EFFAS ‐ EBC and Chinabond Seminar 70 Geneva, 2nd November 2011

Lorenz curves for the different econometric models ROC Curves 1 Tree 0.9 Linear logit Linear logit Linear probit 0.8 Bayesian 11 d 0.7 0.7 nd Chinabon ovember 20 0.6 Cases erence 0.5 0 5 EFFAS ‐ EBC an Default Confe eneva, 2 nd N 0.4 E 0.3 0 3 G 0.2 0 1 0.1 0 0 0.2 0.4 0.6 0.8 1 Non-Default Cases Non-Default Cases EFFAS ‐ EBC and Chinabond Seminar 71 Geneva, 2nd November 2011

Econometric model in action: PD of Promeximbank ‐ Early Warning System Dynamics of Probability of Default 25 20 11 d nd Chinabon ovember 20 15 erence , % EFFAS ‐ EBC an Confe eneva, 2 nd N PD 10 E G 5 0 1998 1999 2000 2001 2002 2003 2004 2005 Month EFFAS ‐ EBC and Chinabond Seminar 72 Geneva, 2nd November 2011

7 CREDIT RATINGS AGENCIES: EXTERNAL CREDIT QUALITY ASSESSMENT CREDIT QUALITY ASSESSMENT EFFAS ‐ EBC and Chinabond Seminar 73 Geneva, 2nd November 2011

Credit ratings agencies Credit ratings agencies • Credit rating agencies are privately organized companies set up to apply ratings to individual debt securities and entire entities that wish to issue bonds within capital markets. The issuers of these wish to issue bonds within capital markets The issuers of these debt securities include publicly traded corporations and distinct branches of government. Bond ratings effectively influence capital 11 d flows by supplying and confirming information to investors A credit flows by supplying and confirming information to investors. A credit nd Chinabon ovember 20 rating measures credit worthiness, or the ability to pay back a loan. erence The top three credit ratings agencies are (all in the United States): • EFFAS ‐ EBC an Confe eneva, 2 nd N Moody's, Standard & Poor's, Fitch Ratings • Each rating agency has developed its own system of rating sovereign and corporate borrowers Fitch Ratings developed a sovereign and corporate borrowers. Fitch Ratings developed a E G rating system in 1924 that was adopted by Standard & Poor's. Moody's grading is slightly different. Moody's sometimes argues that their ratings embed a conceptually superior approach that that their ratings embed a conceptually superior approach that directly considers not only the likelihood of default but also the severity of loss in the event of default EFFAS ‐ EBC and Chinabond Seminar 74 Geneva, 2nd November 2011

Basel 2 and CRAs Basel 2 and CRAs • Under Pillar 1 of Basel II, regulatory capital requirements for credit risk are calculated according to two alternative approaches: – the Standardized Approach; and the Standardized Approach; and – the Internal Ratings ‐ Based Approach. • Under the Standardised Approach (SA) the measurement of credit risk is 11 d based on external credit assessments provided by External Credit based on external credit assessments provided by External Credit nd Chinabon ovember 20 Assessment Institutions (ECAIs) such as credit rating agencies or export credit agencies. erence • • Under the Internal Ratings ‐ Based Approach (IRBA), subject to supervisory Under the Internal Ratings Based Approach (IRBA) subject to supervisory EFFAS ‐ EBC an Confe eneva, 2 nd N approval as to the satisfaction of certain conditions, banks use their own rating systems to measure some or all of the determinants of credit risk. Under the Foundation Version (FV) banks calculate the Probability of Under the Foundation Version (FV), banks calculate the Probability of E G Default (PD) on the basis of their own ratings but rely on their supervisors for measures of the other determinants of credit risk. Under the Advanced Version (AV) banks also estimate their own measures of all the Version (AV), banks also estimate their own measures of all the determinants of credit risk, including Loss Given Default (LGD) and Exposure at Default (EAD). EFFAS ‐ EBC and Chinabond Seminar 75 Geneva, 2nd November 2011

Rating an issue S&P Rating an issue, S&P • In rating an individual debt issue, such as a corporate or municipal bond, Standard & Poor’s p p , typically uses, among other things, information from the issuer and other sources to evaluate the 11 d nd Chinabon credit quality of the issue and the likelihood of ovember 20 default. erence EFFAS ‐ EBC an Confe eneva, 2 nd N • In the case of bonds issued by corporations or municipalities, rating agencies typically begin p , g g yp y g E G with an evaluation of the creditworthiness of the issuer before assessing the credit quality of a specific debt issue EFFAS ‐ EBC and Chinabond Seminar 76 Geneva, 2nd November 2011

Analyzing debt issues S&P Analyzing debt issues, S&P In analyzing debt issues, for example, Standard & Poor’s analysts evaluate, among other things: • The terms and conditions of the debt security and, if relevant, its legal structure. 11 d nd Chinabon ovember 20 • The relative seniority of the issue with regard to the issuer’s other debt issues and priority of repayment in erence the event of default. th t f d f lt EFFAS ‐ EBC an Confe eneva, 2 nd N • The existence of external support or credit enhancements s ch as letters enhancements, such as letters E G of credit, guarantees, insurance, and collateral. These protections can provide a cushion that limits the protections can provide a cushion that limits the potential credit risks associated with a particular issue. EFFAS ‐ EBC and Chinabond Seminar 77 Geneva, 2nd November 2011

Standard & Poor’s ratings Standard & Poor’s ratings Ratings from ‘AA’ to ‘CCC’ may be modified by the addition of a plus (+) or minus ( ‐ ) sign to show relative standing within the major rating categories. • ‘ AAA’ Extremely strong capacity to meet financial commitments. Highest rating 11 d nd Chinabon ovember 20 • ‘AA’ Very strong capacity to meet financial commitments erence • ‘A’ Strong capacity to meet financial commitments, but EFFAS ‐ EBC an Confe somewhat susceptible to adverse economic conditions and h ibl d i di i d eneva, 2 nd N changes in circumstances • ‘BBB’ Adequate capacity to meet financial commitments but • BBB Adequate capacity to meet financial commitments, but E G more subject to adverse economic conditions • ‘BBB ‐ ’ Considered lowest investment grade by market g y participants EFFAS ‐ EBC and Chinabond Seminar 78 Geneva, 2nd November 2011

Standard & Poor’s ratings: g continuation • ‘BB+’ Considered highest speculative grade by market participants • ‘BB’ Less vulnerable in the near ‐ term but faces major ongoing uncertainties to adverse business financial and economic uncertainties to adverse business, financial and economic conditions ‘B’ More vulnerable to adverse business, financial and economic , • 11 d nd Chinabon ovember 20 conditions but currently has the capacity to meet financial commitments erence • • ‘CCC’ Currently vulnerable and dependent on favorable business CCC Currently vulnerable and dependent on favorable business, EFFAS ‐ EBC an Confe eneva, 2 nd N financial and economic conditions to meet financial commitments E • ‘CC’ Currently highly vulnerable ‘ ’ l h hl l bl G • ‘C’ A bankruptcy petition has been filed or similar action taken, but payments of financial commitments are continued payments of financial commitments are continued • ‘D’ Payments default on financial commitments EFFAS ‐ EBC and Chinabond Seminar 79 Geneva, 2nd November 2011

S&P one year performance (2010 Annual Global Corporate Default Study And Rating Transitions) g ) 11 d nd Chinabon ovember 20 erence EFFAS ‐ EBC an Confe eneva, 2 nd N E G EFFAS ‐ EBC and Chinabond Seminar 80 Geneva, 2nd November 2011

Table of correspondence of ratings: p g Moody's, Standard & Poor's, Fitch Ratings 11 d nd Chinabon ovember 20 erence EFFAS ‐ EBC an Confe eneva, 2 nd N E G EFFAS ‐ EBC and Chinabond Seminar 81 Geneva, 2nd November 2011

Ratings and borrowing costs Ratings and borrowing costs • Every company or country that has a rating will be affected in its borrowing costs , at least in public markets. A higher ranking means lower interest rates for the borrower and ki l i t t t f th b d vice versa. The price of credit is set not only by relative credit ratings but also by the general supply of money and credit ratings but also by the general supply of money and 11 d nd Chinabon ovember 20 the specifics of an individual borrowing. erence • A low ‐ rated borrower, for example, can sometimes borrow EFFAS ‐ EBC an Confe eneva, 2 nd N more cheaply by securing the bond with a claim on specific assets, or by paying a third ‐ party to insure the bond. • Conversely, a highly ‐ rated borrower may choose a structure C l hi hl t d b h t t E G that attracts a lower rating because of special characteristics of the issue, including its standing in the characteristics of the issue, including its standing in the borrower's capital structure or the jurisdiction in which it is issued. EFFAS ‐ EBC and Chinabond Seminar 82 Geneva, 2nd November 2011

Controversy Controversy • The high barriers of entry that require large amounts of capital, connections and business reputation eliminate competition from the bond ‐ rating business. Investors titi f th b d ti b i I t believe this lack of competition leads to groupthink, where the major CRAs wrongly assign similar ratings to securities the major CRAs wrongly assign similar ratings to securities 11 d nd Chinabon ovember 20 with little threat of recourse from more intelligent operators. erence EFFAS ‐ EBC an Confe eneva, 2 nd N • CRAs are also paid by the debt issuer to rate bonds and provide advice. This conflict of interest may pressure these firms to assign higher ratings than reality would suggest for firms to assign higher ratings than reality would suggest, for E G the sake of keeping business. CRAs are criticized whenever investment ‐ grade bonds default, as were the events associated with the 2007 ‐ 2009 recession. EFFAS ‐ EBC and Chinabond Seminar 83 Geneva, 2nd November 2011

CRA may have y considerable delay in reaction • Empirical studies have documented that yield spreads of corporate bonds start to expand as spreads of corporate bonds start to expand as credit quality deteriorates but before a rating downgrade implying that the market often leads downgrade, implying that the market often leads 11 d nd Chinabon ovember 20 a downgrade and questioning the informational erence value of credit ratings. value of credit ratings EFFAS ‐ EBC an Confe eneva, 2 nd N • It is even more sluggish for upgrades (see next E G slide). • Not only bonds but also CDS market can provide Not only bonds but also CDS market can provide timely information, if available. EFFAS ‐ EBC and Chinabond Seminar 84 Geneva, 2nd November 2011

Are credit ratings consistent with g credit risk? Case of Alfa Bank (Russia) 11 d nd Chinabon ovember 20 erence EFFAS ‐ EBC an Confe eneva, 2 nd N E G EFFAS ‐ EBC and Chinabond Seminar 85 Geneva, 2nd November 2011

An example: p case of China: Fitch Ratings, 2011 • September 8, 2011 (Reuters) ‐ Fitch Ratings warned on Thursday that it might downgrade China's credit rating within two years as the country's banks struggle with debt loads following a lending surge to help lift the gg g g g p economy during the 2008 financial crisis. • China's long ‐ term local currency rating is AA minus; it could be downgraded over the next 12 to 24 months as Fitch expect a material downgraded over the next 12 to 24 months as Fitch expect a material 11 d nd Chinabon ovember 20 deterioration in bank asset quality. Fitch downgraded the outlook on China's long ‐ term local currency debt to negative from stable in April erence 2011 because of concerns about the country's financial stability following y y g EFFAS ‐ EBC an Confe eneva, 2 nd N a lending surge encouraged by Beijing to help maintain economic growth during the global downturn. • Non performing loans at Chinese banks were about 2 percent of the total, Non ‐ performing loans at Chinese banks were about 2 percent of the total, E G but if lending to local government financing vehicles was appropriately classified, the figure would be more like 6 ‐ 7 percent. • Fitch estimated bank loans would increase this year alone by 18 trillion Fitch estimated bank loans would increase this year alone by 18 trillion yuan. This is the equivalent to 55 percent of China's GDP, which is an extremely high number and a potential problem for banks' asset quality. EFFAS ‐ EBC and Chinabond Seminar 86 Geneva, 2nd November 2011

September 2011 GFSR: opinion about p p China credit performance Still, while they believe it will be costly, most analysts consider that the likely fallout from China’s credit boom will be manageable. One key source of confidence is ill b bl O k f fid i China’s strong fiscal position, including a large stock of public ‐ sector assets and low central government debt public sector assets and low central government debt. 11 d nd Chinabon ovember 20 Nevertheless, even those buffers do not preclude erence significant bouts of uncertainty as to how losses will significant bouts of uncertainty as to how losses will EFFAS ‐ EBC an Confe eneva, 2 nd N ultimately be allocated among the banks’ private investors and local and central governments. To the E extent that the government needs to step in, the h h d i h G consequence could be a substantial worsening of China’s public debt metrics and a narrower scope for future public debt metrics and a narrower scope for future fiscal stimulus. EFFAS ‐ EBC and Chinabond Seminar 87 Geneva, 2nd November 2011

Nationally Recognized Statistical y g Rating Organizations (U.S.) • In of 2009 the U.S. Securities and Exchange Commission (SEC) has identified ten Nationally Recognized Statistical Rating Organizations (NRSRO) that are registered by the Commission to rate financial institutions, corporations, asset ‐ backed securities and government debt for sale in the United States. Fitch, Moody's and i i d d b f l i h U i d S Fi h M d ' d Standard & Poor's are the most recognized credit rating agencies (CRA) in America and account for the majority of the market share within the bond rating industry. 11 Firms currently registered as NRSROs are: Firms currently registered as NRSROs are: d nd Chinabon ovember 20 – A.M. Best Company, Inc. – DBRS Ltd. erence – Egan ‐ Jones Rating Company EFFAS ‐ EBC an Confe eneva, 2 nd N – Fitch, Inc. – Japan Credit Rating Agency, Ltd. – Kroll Bond Rating Agency, Inc. (f/k/a LACE Financial Corp.) – Moody s Investors Service, Inc. Moody’s Investors Service, Inc. E G – Rating and Investment Information, Inc. – Realpoint LLC – Standard & Poor’s Ratings Services The US Congress and other regulatory agencies have since required that banks and institutional investors only buy bonds rated investment ‐ grade (those giving ratings of BBB or higher) by one of the NRSROs . The license has been a boon to the NRSROs. EFFAS ‐ EBC and Chinabond Seminar 88 Geneva, 2nd November 2011

National CRA in Russia recognized by government • For the first time in 2010 in Russia seven rating agencies ‐ three international and four Russian ‐ received official government accreditation by Ministry of Finance. y y • In assessing the reliability of certain assets, restrictions or increase their investments in pension funds, placing of state corporations will pay attention and recognize only the opinions of these market participants. attention and recognize only the opinions of these market participants. 11 d nd Chinabon ovember 20 These are – international agencies: Moody s Investor Service, Fitch Ratings, Standard & erence Poor s. Poor s. EFFAS ‐ EBC an Confe eneva, 2 nd N – Russian agencies: National rating agency, AK & M, RusRating agency and "Expert RA". • With regard to the seven rating agencies and the Ministry of Finance With regard to the seven rating agencies and the Ministry of Finance E G Central Bank opinions match. • Our presentation concerning statistical analysis of credibility of ratings assigned by Russian CRA is available as complementary material assigned by Russian CRA is available as complementary material EFFAS ‐ EBC and Chinabond Seminar 89 Geneva, 2nd November 2011

CRA in China CRA in China • Since 2003, insurance companies and the National Council for Social Security Fund, were given permission to invest in highly rated domestic corporate bonds by an authorized credit rating firm; the National Development and Reform Commission authorized credit rating firm; the National Development and Reform Commission indicated that corporate bonds issued from that point forward could only be rated by an agency which had already provided a domestic bond rating since the year 11 d 2000.As of 2008, the accredited agencies were 5: China Chengxin Credit Rating Co. 2000 A f 2008 h di d i 5 Chi Ch i C di R i C nd Chinabon ovember 20 ( 中 � 信 ), Dagong Rating Co. ( 大公 ), China Lianhe Credit Rating Co. (� 合 ), Shanghai erence Brilliance Credit Rating & Investors Service ( 上海新世 �), Shanghai Far East ( 上海 �� EFFAS ‐ EBC an Confe eneva, 2 nd N ) • Since China has not permitted foreign credit rating agencies to rate locally issued bonds independently , they have had to access the market through partnerships bonds independently they have had to access the market through partnerships E G with one of these local agencies. In particular, In 1999, Fitch and China Chengxin started a joint venture, China Chengxin International, but their arrangement collapsed in 2003 Mood ’s collapsed in 2003. Moody’s, which had a technical co ‐ operation agreement with hich had a technical co operation agreement ith Dagong in the late 1990s, eventually replaced Fitch in 2006 and reconstituted China Chengxin International with China Chengxin. EFFAS ‐ EBC and Chinabond Seminar 90 Geneva, 2nd November 2011

8 INTERNAL CREDIT RATINGS EFFAS ‐ EBC and Chinabond Seminar 91 Geneva, 2nd November 2011

What should be an ideal internal credit rating system • A number of rating techniques and methodologies have evolved over time. The methodologies range from a spectrum of purely expert/professional judgment f l / f l d taking into account only qualitative factors, to a 11 sophisticated statistical model based methodology sophisticated statistical model based methodology d nd Chinabon ovember 20 solely taking into account the quantitative factors. erence • Although the degree of subjectivity becomes lesser • Although the degree of subjectivity becomes lesser EFFAS ‐ EBC an Confe eneva, 2 nd N with the movement on the spectrum towards statistical methods, yet neither of the two extremes is advisable. , y E G An ideal internal risk rating system is based on both quantitative and qualitative factors concluding the decision based on many different attributes, involving d i i b d diff ib i l i the human judgment. EFFAS ‐ EBC and Chinabond Seminar 92 Geneva, 2nd November 2011

Rating systems that combine g y models with judgment In practice, many banks use rating systems that combine models with judgment. Two approaches are common. Judgmental systems with quantitative guidelines or model results as Judgmental systems with quantitative guidelines or model results as • inputs. Historically, the most common approach to rating has involved individuals exercising judgment about risks, subject to policy guidelines containing quantitative criteria such as minimum values for particular containing quantitative criteria such as minimum values for particular 11 d nd Chinabon ovember 20 financial ratios. Banks develop quantitative criteria to guide individuals in assigning ratings, but often believe that those criteria do not adequately erence reflect the information needed to assign a rating. g g EFFAS ‐ EBC an Confe eneva, 2 nd N • Model ‐ based ratings with judgmental overrides. When banks use rating models, individuals are generally permitted to override the results under certain conditions and within tolerance levels for frequency. Credit ‐ rating certain conditions and within tolerance levels for frequency. Credit rating E G systems in which individuals can override models raise many of the same issues presented separately by pure judgment and model ‐ based systems. If overrides are rare, the system can be evaluated largely as if it is a model ‐ , y g y based system. If, however, overrides are prevalent, the system will be evaluated more like a judgmental system. EFFAS ‐ EBC and Chinabond Seminar 93 Geneva, 2nd November 2011

Portfolio level Portfolio level • Whatever the method used, the result of the evaluation should be in such a shape that provides meaningful information which can be further used for effective credit risk measurement and further used for effective credit risk measurement and management of the credit exposure at an individual level as well as at a portfolio level 11 d • Ri k Risk rating process must provide for a meaningful differentiation of i id f i f l diff i i f nd Chinabon ovember 20 risk, grouping of satisfactory homogenous exposures, and must erence allow for accurate and consistent estimation of loss characteristics EFFAS ‐ EBC an Confe eneva, 2 nd N at pool level . • The internal risk rating system should be integrated with other systems of the banks such as portfolio monitoring loan loss systems of the banks such as portfolio monitoring, loan loss E G reserves analysis for provisioning, pricing of the loan, internal capital planning and return on capital analysis. Banks should not use separate rating systems for lending purposes risk quantification separate rating systems for lending purposes, risk quantification (cardinal scale assessment) and capital allocation. EFFAS ‐ EBC and Chinabond Seminar 94 Geneva, 2nd November 2011

Two tier rating system Two tier rating system. The internal risk ratings should be based on a two tier rating system. g y 1. An obligor rating, based on the risk of borrower default and representing the probability of default by a p g p y y 11 d nd Chinabon ovember 20 borrower or group in repaying its obligation in the erence normal course of business and that can be easily EFFAS ‐ EBC an Confe eneva, 2 nd N mapped to a default probability bucket. 2. A facility rating, taking into account transaction f y g, g E G specific factors, and determining the loss parameters in case of default and representing loss severity of principal and/or interest on any business credit facility. EFFAS ‐ EBC and Chinabond Seminar 95 Geneva, 2nd November 2011

Obligor ratings Obligor ratings • In order to assign obligor ratings the banks are required to consider, but not limited to, the following aspects of the borrower: • • Financial Condition Financial Condition – Economic and financial situation – Leverage g 11 d nd Chinabon ovember 20 – Profitability erence – Cash flows EFFAS ‐ EBC an • M Management and ownership structure t d hi t t Confe eneva, 2 nd N – Ownership structure – Management and quality of internal controls Management and quality of internal controls E G – Promptness/ assessment of the willingness to pay – Strength of Sponsors • I d Industry properties and sector of business t ti d t f b i • Country risk (if appropriate) EFFAS ‐ EBC and Chinabond Seminar 96 Geneva, 2nd November 2011

Facility ratings Facility ratings • In order to assign the facility ratings, the bank should consider the relevant and material information including : Facility Facility • – Nature and purpose of loan – Product type and structure 11 d – Priority of rights in case of bankruptcy P i it f i ht i f b k t nd Chinabon ovember 20 – Degree of collateralization erence – Composition of collateral EFFAS ‐ EBC an Confe eneva, 2 nd N • Collateral – Nature and Quality – Liquidity q y E G – Market value – Exposure of the collateral to different risks – Legal status of rights – Legal status of rights – Legal enforceability – Time required to dispose of EFFAS ‐ EBC and Chinabond Seminar 97 Geneva, 2nd November 2011

Qualifying rating system for IRB Qualifying rating system for IRB • Rigorous credit risk measurement is a necessary element of advanced risk management. Qualifying institutions will use their internal rating systems to associate a probability of default (PD) internal rating systems to associate a probability of default (PD) with each obligor grade, as well as a loss given default (LGD) with each credit facility. In addition, institutions will estimate exposure at 11 d default (EAD) and will calculate the effective remaining maturity (M) default (EAD) and will calculate the effective remaining maturity (M) nd Chinabon ovember 20 of credit facilities. erence Qualifying institutions will be expected to have an IRB system • EFFAS ‐ EBC an Confe eneva, 2 nd N consisting of four interdependent components: – A system that assigns ratings and validates their accuracy, – A quantification process that translates risk ratings into IRB – A quantification process that translates risk ratings into IRB E G parameters, – A data maintenance system that supports the IRB system, – Oversight and control mechanisms that ensure the system is O i h d l h i h h i functioning as intended and producing accurate ratings . EFFAS ‐ EBC and Chinabond Seminar 98 Geneva, 2nd November 2011

Standards for IRB rating systems Standards for IRB rating systems Institutions have to comply in designing and operating IRB rating systems subject to five broad standards: • Two ‐ dimensional risk ‐ rating system – IRB institutions must be able to make g y meaningful and consistent differentiations among credit exposures along two dimensions—obligor default risk and loss severity in the event of a default. • Rank order risks – IRB institutions must rank obligors by their likelihood of default, 11 d and facilities by the loss severity expected in default. d f ili i b h l i d i d f l nd Chinabon ovember 20 Calibration – IRB obligor ratings must be calibrated to values of the probability of • erence default (PD) parameter and loss severity ratings must be calibrated to values of the loss given default (LGD) parameter loss given default (LGD) parameter. EFFAS ‐ EBC an Confe eneva, 2 nd N • Accuracy – Actual long ‐ run actual default frequencies for obligor rating grades must closely approximate the PDs assigned to those grades and realized loss rates on loss severity grades must closely approximate the LGDs assigned to those on loss severity grades must closely approximate the LGDs assigned to those E G grades. • Validation process – IRB institutions must have ongoing validation processes for rating systems that include the evaluation of developmental evidence, process rating systems that include the evaluation of developmental evidence, process verification, benchmarking, and the comparison of predicted parameter values to actual outcomes (back ‐ testing). EFFAS ‐ EBC and Chinabond Seminar 99 Geneva, 2nd November 2011

9 BOND SPREADS AND RISK FREE ZERO COUPON YIELD CURVE ZERO ‐ COUPON YIELD CURVE EFFAS ‐ EBC and Chinabond Seminar 100 Geneva, 2nd November 2011