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20080319_Essex_1_2003.ppt Credit Portfolio Management A practioners view Bruno De Cleen Essex, March 19 2008.

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Presentation on theme: "20080319_Essex_1_2003.ppt Credit Portfolio Management A practioners view Bruno De Cleen Essex, March 19 2008."— Presentation transcript:

1 20080319_Essex_1_2003.ppt Credit Portfolio Management A practioners view Bruno De Cleen Essex, March 19 2008

2 20080319_Essex_1_2003.ppt 2 Introduction The purpose of this material is to give some input for a discussion about capital and portfolio management, a domain where theory and practice meet. The dominant perspective is that of a M, L, XL commercial bank in continental Europe I would like to demonstrate that things get already complicated before the mathematics become difficult. Therefore I invite you to put one step back. I have deliberately left out all the more technical and mathematical aspects. As this is rather a high level overview, things have been considerably simplified and therefore may lack accuracy. The opinions expressed in this document are solely the authors and do not necessarily reflect those of my current or previous employers. Any graphs or tables shown are based on mock data and are for illustrative purposes only.

3 20080319_Essex_1_2003.ppt Retail Private Banking SME Publc Sector A Commercial Bank (extended) 3 Executive Board Audit Finance/Risk Corporate Specialised Finance Corporate Finance Private Equity Financial Markets Asset Management Real Estate Insurance IT HR Operations

4 20080319_Essex_1_2003.ppt Financial Sector Funding Deposits Without term Term Equity Tier 2 (retained earnings) Tier 2 (Subordinated Debt) Loans Property The simplified balance sheet 4 Bank B/S ReceivableLiability Off Balance ALM Risk Liquidity Risk Credit Risk Market Risk Solvency Requrirements Basel 1 – Basel 2 Target Capital Rating Agencies Capital

5 20080319_Essex_1_2003.ppt All flavours and formats of Credit Risk 5 Bullet Amortising Revolving Funded Counterparty risk for Derivatives Unfunded Loans Overdraft facilities CDS Guarantees Wide variety of risks Rental guarantee Bidbond, Performance bond etc. Leverage Tranches Investment Hedging Legal Format Jurisdiction Confirmed vs not confirmed Immediately cancellable

6 20080319_Essex_1_2003.ppt Very different types of exposures 6

7 20080319_Essex_1_2003.ppt Geographical Concentration as a rule 7

8 20080319_Essex_1_2003.ppt Risk/Solvency Measures 8 Expected Loss VAR (1-x bps) Unexpected Loss Economic Capital VAR has some conceptual shortcomings which however in practice dont cause too much problems Calculation in the tail is difficult Small changes in parameters can have large impact Basel 1 regime for credits was fairly arbitrary (100, 50, 20 % weightings) Basel 2 (pillar 1), Internal Ratings based Approach, calculates solvency requirements in an economic capital way. Economic Capital Basel 2 The main perceived shortcomings as to solvency for credit risk are: Imposed correlations Structured products Assumed single name concentration adjustment Unclear mild crisis calibration Various imposed caps and floors Transition Regime: Floor of 90/80% of old Basel 1 regime

9 20080319_Essex_1_2003.ppt 9 Risk Tolerance and relevant risk measures P&L Volatility Rating agencies capital) Economic Capital Going Concern Failure Solvency insufficiency B1,B2 Downgrading Event or series of events hitting the the front page Inquiry by Stakeholders Insolvency Regulator Deposit Holders Management Shareholders Different stakeholders have different focus and different risk tolerance The same amount of loss can have different impact depending on the fact whether the loss has been realised inside or outside the core business or the strategic business plan communicated to the market Ex ante loss tolerance tends to be bigger than ex-post loss tolerance Human beings tend to be bad at handling probabilistic choices. They prefer real dollars to wooden dollars. They tend to have a linear approach.

10 20080319_Essex_1_2003.ppt Return Calculations 10 Return on Assets Return on Equity Return on Capital Return on Required Equity B! And B2 TraditionalRaroc + Income - Cost - Expected Loss + Capital Benefit - Taxation ------------------------ Risk Adjusted Net Profit / Economic capital =>Raroc percentage + Income - Cost - Losses and provisions + Capital Benefit - Taxation - ------------------------ Risk Adjusted Net Profit / Capital or Assets => percentage Economic Profit Risk Adjusted Net Profit - Economic capital * Cost of Captital --------------------------- =>Economc Profit amount In practice many hybrid concepts are used Different measures are used simultaneously Even if called the same, calculations can be very different

11 20080319_Essex_1_2003.ppt 11 The Spectrum of Credit Portfolio Approaches Name level notional limit management based on rating grade/ industry Limits set by board level credit committees CDS used to hedge excess exposure Name level notional limit management supplemented by economic capital limits RAROC based objectives Hedge names or sectors that breach limits using CDS, indices or baskets/ nth to default Economic/ regulatory capital driven securitisations Centralised view of credit risk RAROC based objectives but recently overlaid by a mark to market view due to IFRS/ fair value acc. Migrate to the optimal portfolio Overlay macro views on credit, CPPI structures Exposure management systems Credit rating tools LGD tools Credit portfolio models that aggregate and dis-aggregate risk to individual issuers/ sectors Ability to evaluate the impact of single name and basket hedges Ability to evaluate the impact of hedging using tranches, proxy- hedges, CPPI Ability to evaluate the MtoM volatility of the hedge book Limit Management Economic/ Regulatory Capital Management Profit Centre/ Credit Treasury Default view MtoM/Total Return view

12 20080319_Essex_1_2003.ppt The Building Blocks of Credit Risk Modelling 12 PD Probability of default EaD Exposure at Default LGD Loss Given Default Dependency Limited number of observed defaults for some populations Lack of consistency Default definitions Legacy systems Calibration issues Consistency in calibration over different populations Limited number of years of history Group effects Limited to extremely limited number of observations Often bimodal distributions Lose a lot Lose almost nothing All types of Randomness Amortising loans versus growing portfolios Revolving exposures Counterparty risk in derivative transactions Default correlations almost not directly observable Independency building blocks If not foreseen by construction, a positive definite matrix is often already quite a performance What about dependency if things get really sour Looking for the perfect copula

13 20080319_Essex_1_2003.ppt PD Modelling 13 Randomness is quite an obstacle A small change on the side of the highest PDs implies a massive change of the distribution Rank ordering is most of the time fairly all right Estimates from models and experts tend rather to converge Rank Ordering Calibration Limited to extremely limited number of observations A patchwork of different populations Very different techniques used Qualitative vs quantitative or expert based Producing PDs Ratings mapped to PDs Events perceived as default triggers can vary over different popoulations 90 days pas due in consumer finance 1 day past due on an interest payment in the bond market Grace period in shipping... Harmonisation across the portfolio is very hard Portfolio Patchwork

14 20080319_Essex_1_2003.ppt Dependency structures: (Proxy) n 14 Portfolio Segment Geography Segment Reference Population Dependency data mainly available for US corporate or for listed corporate. The Banks portfolio is mainly is European, non listed, with lots of retail Data are bucketed along a few dimensions => does not fit the required dimensions Asset Values+ Equity Values Information derived not from defaults but from equity or asset values

15 15 Randomness Inconsistency in methodology used Correlation impact When looking at default statistics, drawing conclusions is often less straight forward than one would have hoped

16 20080319_Essex_1_2003.ppt LGD Modelling 16 Often Bimodal Technical defaults returning to the healthy portfolio Often a re-start can be envisagead; Liquidity/capital injection Carving out the unhealthy part of the business, Bank loans often with good collateral as compared to bonds Independency with PD often questionable e.g. Asset based finance

17 20080319_Essex_1_2003.ppt Credit risk may be fairly complex to assess 17 Company A Company DCompany B Joint venture SPE Company C Group Structures are often complex Unclear where a group starts and where it ends Co-debtorship, Guarantees and Letters of intent of all sorts => what to think about PD and LGD ? Ring fenced structures Difficult to tell what economic sector Group Structures Geography Greek Owner Liberian Flag Sailing all over the globe The Main client is a Russian Company A Collecting Account in the US Insurance in the UK There is no simple/unique answer to the question what geographical risk the ship financing is exposed to.

18 20080319_Essex_1_2003.ppt Credit Risk Modelling = looking for the adequate compromise 18 Business Acceptance Market consistency Robustness Methodological integrity Criteria Choices Default versus MtoM Horizon Point in Time (PIT) versus through the cycle (TTC) Instruments/Hedges forced in framework or Portfolio expressed in Marketable instruments (replicating portfolio) Objectives and Use Trading (bps market consistent) Solvency (order of magnitude) Identification of concentration Hedging Diversification Strategic choices

19 20080319_Essex_1_2003.ppt Accounting Complexity: What you see is what you get? 19 Main regimes for assets with credit risk Fair value through Profit & Loss Available for Sale/ Fair value through Equity Loans and receivables Assets Balence Sheet P&L Assets Balence Sheet Equity Assets Balence Sheet P&L - Impairment

20 20080319_Essex_1_2003.ppt Accounting: The Hedging Trap 20 Assets Balence Sheet P&L Value of the book hedged Economic value of the combined position Economic view Accounting view Asymmetrical accounting treatment of the book hedged and the hedging instrument shows increase volatility where it has been economically reduced

21 20080319_Essex_1_2003.ppt The Main Levers of Portfolio Management 21 Front DoorBack Door Limits Pricing Incentive systems Acquisitions Securitisation Swaps/Pooling Derivatives Diversification/Overlay Investments Derivatives L/S Beta Overlays X-Asset class

22 20080319_Essex_1_2003.ppt Securitisation 22 Reference or Transferred Portfolio Total Portfolio Notes Mezzanine Super Senior AAA The dominant factors in the business case are usually Funding cost Liquidity Regulatory Capital Relief The rationale behind regulatory capital arbitrage is fairly simple: the purpose of the exercise is to free-up capital at a cost that is lower than the cost of raising new capital in the market Risk transfer and economic capital savings are often difficult to calculate (CDO 2 ) No solution for tall trees Not all types of assets are suitable Operational complexity / infrasturcture An extremely wide variety of structures: Synthetic transactions versus true sales Synthetic usually partially funded (SPV) B1 to B2 transition

23 20080319_Essex_1_2003.ppt Main Hedging/Credit Spread Tools InstrumentAdvantagesDisadvantage B 1B 2 ECap CostMtoM Corporate Single- Name Credit Default Swaps Isolates credit risk and best tool for tall trees Liquidity and transparency Basis between loan and bond underlying Loan Credit Default Swaps More efficient hedging/ ideal for tall trees Can be non mark to market Developing market, lack of liquidity Non cancellability/ no restructuring Highly liquid instruments Ability to put on large macro hedges CDS indices Cost and roll down No capital relief except where names overlap Swaptions on CDS indices Potential for lower cost and mark to market compared to CDS Single name market is not liquid Ability to pinpoint macro hedges to lower cost Market well balanced and liquid Tranches on CDS indices Non linear risk Impacted by market technicals Remark: predominantl y a pre-credit crisis view

24 20080319_Essex_1_2003.ppt The Complexity of working with credit derivatives or Where is Omicron * 24 The Greeks and the like Delta Gamma etc. Jump to default Cliff risk? Basis Risk Spread difference Bond-CDS But more general difference between position hedged and hedging instrument. Most hedges when looked at properly turn out to be proxy hedges The Hedge stand alone versus the combined position MtoM view and Accounting view (if different) Operational aspects Timely evaluation based on real market prices Operational speed and accuracy Views * Omicron is the undiscovered Greek character feared by all modellers

25 20080319_Essex_1_2003.ppt Specific Trading Models What about the universal or ultimate Credit Portfolio Model? 25 Overall Portfolio Model Specific Trading Models Portfolio Patchwork Credit Portfolio Environment Market Intstruments Market Environment Overall view Low frequency of update Patchwork Order of magnitude ambitions Specific product view High frequency of update Focused – Pure Bps ambitions How not to get ripped off on the Bps How not to save Bps while missing the point on the effectiveness of the hedge

26 20080319_Essex_1_2003.ppt Important Modelling Choices Portfolio Patchwork Portfolio Model Hedges Force Market Instruments into Model Logic Market Vaue Express Portfolio in Marketable Instruments Portfolio Patchwork Hedges Replicating Portfolio Portfolio Model One Step Approach Replicating Portfolio Static Hedges ? Dynamic Hedges?

27 20080319_Essex_1_2003.ppt EVA-Raroc The transaction as such Alternative use of the space liberated Funding cost Risk Transfer Solvency relief Reduction of P&L vol Eg. Reduction of concentrationl Liquidity - diversification Legal/Documentation Taxation Accounting interpretation Operational Aspects Reputational Risk LT effects ST effects Transition from one regime to another 27 Assessment of Back-end Transactions is complex Quantitative Qualitative or Difficult to Quantify Time Alternative solutions (Back-end – Front End) Business Perspective – Group Perspective

28 20080319_Essex_1_2003.ppt 28 Concluding remarks Things get already complicated before the mathematics become difficult. Sometimes the stochastic differential equations is the funny part of the exercise. Although I am a great fan of modelling, I would like to invite you to keep your eyes open for its limitations. Beware of apparent precision. Due to lack of data, assumptions (explicit and … implicit) have great impact Sometimes but fortunately not always, more advanced mathematical techniques dont make things any better. Sometimes it is even quite the opposite. Beware of the cookbook approach. The value is to be found not in the formulas but in the rigorous thinking. Dont underestimate the importance of regulations, accounting and legal. Communication with all stakeholders is a crucial but a difficult exercise. A Master in Common Sense and a PhD in Applied Modesty are great qualifications on top of the necessary degrees in maths, stats, physics, financial engineering or econometrics.

29 20080319_Essex_1_2003.ppt 29 Addional Slides

30 20080319_Essex_1_2003.ppt 30 Capital Management Activities Quantitative Assessment of -Basel I -Basel II -Rating Agencies -Economic Capital Capital Assessment Capital Adequacy and Planning Capital Market Transactions Capital Optimisation Stakeholder Communication Monitoring Regulatory, economic and rating agency capital levels Forecasting and scenario analysis linked to strategic planning Issuance - Tier 1 - Tier 2 Transactions -Risk transfer -Diversification -Risk taking Input into strategic planning process to risk taking (within Risk appetite) Optimisation possibilities Input Initiative Steering Internal - Senior management - Other departments External - Local Banks - Investors/analysts - Rating agencies, regulators, CPM Involvement Credit The simplified ICAAP View

31 20080319_Essex_1_2003.ppt 31 Typical CPM roles/activities at the Group level Keep books on the Group level Provides operational and administrative support on the group level Collect, roll out and ensure use of consistent CPM best practices within BU CPM functions Provide selective CPM functionality for Business Units without dedicated CPM unit Represent all CPM activities internally and externally (e.g. in IACPM meetings) Represent Business Unit CPM across the group Develop market transaction competence Periodically build and report global Group credit exposures Monitor portfolio developments and report major changes to management Conduct stress tests on Global level Highlight significant breaches of group- wide credit risk limits Propose immediate action when required in order to shield the portfolio from severe value losses Monitor BU CPM activity Monitor BU origination policies and initiate improvements if needed Develop portfolio optimisation strategies in order to enhance group risk/return profile from a neutral perspective (including limited investments) Propose actions if alarming concentrations on Group level occur Propose, design and manage transactions delivered on a group level Involvement in strategy and budget process (esp. capital management) Recommend group-wide exposure limits (name, industry & country level) Input into policy formulation and review process Set guidelines for credit risk related stress testing within Bus Contribute to determination of Rabos risk appetite and capital allocation strategy Risk Aggregator:Manager of Credit Risk: Enabler Controller Policy Contributor Centre of Competence

32 20080319_Essex_1_2003.ppt 32 Capital management activities both to secure and to optimise going concern Capital Budgets Limits Hedge Process Contingency Forecast Policies STOP Guideline Growth Profit Optimise Going Concern Secure Going Concern


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