Risk Capital Framework

A Practical Approach to Risk Capital Allocation and Charging

Soren Lautrup Paul Stefiszyn Amsterdam, 13 June 2013

About Us

Soren Lautrup Director, ESP Consulting UK • Over 20 years' experience in advising leading utilities on strategy, energy trading and risk management, and a wide range of commercial and contractual issues. • Significant track-record in advising governments, regulators and market participants on trading arrangements and industry reform in both mature and emerging markets. • Before founding ESP Consulting, Partner at PA Consulting, where he led the UK utilities team advising clients across Europe. • Previously a Director with PwC Consulting where he led a pan-European specialist team advising on energy trading and risk management. • Soren is also one of the founding members of the European Energy Risk Forum which brings together risk practitioners from leading European utilities and energy companies.

Paul Stefiszyn Director, ESP Consulting Benelux • Expert in commodity risk management with over a decade of experience in risk modelling, valuation, and risk control. • Advises industrial and trading clients on the practical implementation of best-practice risk management: – policy development; – specification of risk reporting; – implementation of risk models; – design of the Risk Management organisation and capacity building; – trading and risk system requirements; and – business process design and optimisation. • Before joining ESP Consulting Paul held several senior Risk Management roles at Nuon Energy, a vertically integrated energy utility and trading operation. 2 About ESP Consulting

Where we work What we do

Our offices Our services • ESP Consulting UK Led by Soren Lautrup, We provide consultancy services to energy Andrew Chattrabhuti & companies, utilities, governments and Alistair Green regulators in the UK and Europe, covering: • ESP Consulting Benelux • Energy Trading & Risk Management Led by Paul Stefiszyn • Wholesale Market Policy & Reform • ESP Consulting Nordics • Market Strategy & Organisational Led by Claus Hartmann Improvement & Michael Sanggaard • Networks Regulation • Wind Development

Some recent clients

3 This guy has a problem …

How can I align our How can I measure business actions with business performance on our risk appetite ? a risk-adjusted basis ?

How can I link incentive How can I achieve compensation to risk our debt rating control and efficient objective ? risk-taking ?

How can I set risk How can I evaluate the limits that are risk/reward balance consistent with when selecting business targets ? opportunities ? Agenda

• Proposal for a Risk Capital Framework • Quantifying Risk Appetite and Risk Capital – Articulating a quantitative measure for risk appetite – Linking risk appetite directly to business objectives and balance sheet metrics – Converting risk appetite to a measure of Risk Capital • Risk Capital Measurement and Budgeting – Linking corporate objectives to the day-to-day operational management of the business – Creating a consistent basis for allocating group level Risk Capital to operational limits (e.g. VaR limits) – Addressing key challenges in measuring the utilisation of Risk Capital across multiple risk factors (e.g. market, credit, operational, and liquidity risks) and business areas • Risk Capital Charges – Identifying the real (as opposed to notional) costs attributable to Risk Capital at a corporate level – Highlighting key considerations in designing a practical framework for internal risk charging

5 Proposal for a Risk Capital Framework Introduction to Risk Capital Basic Definitions

• In its most general form, Risk Capital (or Economic Capital) is often defined as: “the potential economic loss of an activity regardless of the level of funds committed.” • But there are plenty of (more prescriptive) definitions available, for example: – “Risk capital is the amount of capital required to absorb potential unexpected economic losses, resulting from extremely severe events over a one-year time period.” – “a measure which requires sufficient capital to remain solvent (on a market-consistent basis) with 99.5% confidence at a 1-year horizon” • Some utilities adopt an approach not dissimilar to the last definition, using the annual default probability consistent with the actual or desired credit rating as the confidence level • Another fairly common approach is to apply CAD standards as a proxy for risk capital: – Under CAD II, Risk Capital is therefore estimated as VaR at 99% confidence for a 10 day holding period multiplied a buffer (3-4) – Offers a mechanistic and simple way to measure capital – Virtually all energy companies operate VaR risk engines for all or part of their portfolio from which the CAD requirements can be computed

7 Proposal for a Risk Capital Framework Our Definition

• Our objective is to outline a practical approach which places Risk Capital as the anchor for the operational control framework • This approach assumes that the dominant corporate objective is to maintain a rating at or above investment grade (Baa/BBB) • The key risk which this approach seeks to manage is a (single) downgrade, not the ultimate demise of the company. • In turn this requires that the Risk Capital concept: - Captures risk (earnings volatility) over timeframes which correspond to the corporate budget and planning cycle. - Is directly linked to the risk limits and controls which govern how the business operates on a day-to-day basis • Under this tighter standard, Risk Capital is therefore the maximum annual loss that can be tolerated at a defined confidence level without jeopardising ratings performance

8 Proposal for a Risk Capital Framework The Framework

Risk Risk Target Rating Capital Appetite

Positions & Limits & Exposures Measurement Controls and Control

Deriving a top-down Estimate Allocate risk limits to Estimate the cost Translate such costs quantitative measure bottom-up the business of Risk Capital at into charges which of risk appetite and demand for risk operationally, the corporate can be applied capital consistent with capital across consistent with the level across the business. ratings targets the business Risk Capital metric

9 Quantifying Risk Appetite and Risk Capital Setting Risk Appetite Overview

• Proposed approach ties Risk Appetite directly to target rating performance

Target Rating

1 6 Target Required Confidence Financial metrics for meeting targets

2 Corresponding 7 8 Debt/EBITDA Ratio Risk Appetite Risk Capital

3 Target Minimum EBITDA & Maximum Debt 5 Target 4 Maximum Loss Budget EBITDA & Debt

• Review of Risk Appetite and Risk Capital allocation part of annual budgeting cycle • Can readily be explained and communicated to BoD and Execs • Easy to compute (no black boxes)

11 Setting Risk Appetite Why Focus on External Rating?

• Arguably the single biggest risk faced by many companies, in particular those close to the investment grade cliff-edge • In addition, the criteria and methodologies applied by the rating agencies in assessing the credit worthiness of companies provide a good benchmark and consistent framework for: – Analysing the relative importance of the multitude of factors which enter into this assessment; and – Consolidating these factors in a single target credit rating which in turn can be linked to a quantitative metrics for Risk Appetite. Moody’s rating of 52 unregulated utilities and power companies (March 2013):

10

8

6

4 No of Companiesof No 2

0 Aaa Aa1 Aa2 Aa3 A1 A2 A3 Baa1 Baa2 Baa3 Ba1 Ba2 Ba3 B1 B2 B3 Caa1

Investment Grades Speculative (Junk) Grades

12 Setting Risk Appetite Ratings Criteria

• Following uses Moody’s ratings methodology for Unregulated Utilities

Ratings Criteria for Unregulated Utilities

Category Weight Assessment Focus

Scale & Competitive Position (25%) • Size and Scale 15.0% • Corporate strategy and fit with the business as it can • Competitive Position and market structure 10.0% be observed Cash Flow Predictability of Business Model (25%) • Fundamental value drivers and competitive positioning • Fuel strategy & Mix 5.0% • Synergies (or lack thereof) across group wide portfolio • Degree of Integration & Hedging strategy 5.0% of assets and positions • Capital Requirements & Operational Performance 5.0% • Contribution from low-risk (i.e. regulated) businesses 10.0%

Financial Policy (10%) 10.0% • Financial stability and leverage Financial Strength (40%) • Sustainable cashflow and (long term) ability to service • Funds From Operations /Interest 10.0% debt • Funds From Operations / Debt 12.5% • Retained Cashflow / Debt 12.5% • Hard financial metrics • Free Cashflow / Debt 5.0%

Source: Moody’s ratings methodology for unregulated utilities and power companies

13 Setting Risk Appetite Financial Strength Metrics

• Table sets out Moody‘s Financial Strength Criteria, which are assessed against previous 3 financial years:

Metric Aaa Aa A Baa Ba Interest Cover1) >=15x 9x - 14.9x 6x - 8.9x 3.5x - 5.9x 1.8x - 3.4x FFO/ Debt2) >=70% 45% - 69% 28% - 44% 17% - 27% 10% - 16% RCF/ Debt3) >=50% 32% - 49% 20% - 31% 12% - 19% 7% - 11% FCF/Debt4) >=50% 20% - 49% 10% - 19% 0% - 9% 0% - (15%)

1) Cash Flow from Operations (CFO) less Changes in Working Capital + Interest divided by Interest + Capitalized Interest 2) FFO or CFO less Changes in Working Capital divided by Total Debt 3) FFO/CFO less Dividends (and Minority Interest if present) divided by Total Debt 4) FFO/CFO less Dividends less Capital Expenditures divided by Total Debt. • Metrics could be computed for current budget assumptions, but may be more readily understood and interpreted if converted to EBITDA (or Gross Margin) metrics • Possible to derive Debt/EBITDA ratio consistent with these criteria using (company specific) historic or budgeted ratio between cashflow (FFO) and EBITDA • This enables targets to be derived for minimum EBITDA (given debt) or maximum debt (given EBITDA) consistent with the Financial Strength metrics • These targets can then be compared directly with budgeted EBITDA and debt for future years

14 Setting Risk Appetite A Worked Example

Budget € Mill • Consider a utility with a target of maintaining at least an Net Debt 2,700 Budgeted EBITDA 800 investment grade rating (i.e. Baa/BBB) Interest Expense 135 Capitalised Interest - • Given the budget assumptions in the right-hand box, the Change in Working Capital 60 Debt/EBITDA ratios consistent with each strength metric are: Forecast Capex 300 Forecast Dividends 81

All numbers € Mill Budgeted EBITDA/FFO Ratio 1.18 Metric Aaa Aa A Baa Ba Interest Cover Metric Implied FFO >1890 1080 - 990 675 - 1080 338 - 675 338 - 108 Implied EBITDA >2230 1274 - 1168 797 - 1274 398 - 797 398 - 127 Implied Debt/EBITDA <1.21 2.12 - 2.31 3.39 - 2.12 6.78 - 3.39 6.78 - 21.19 FFO/ Debt Metric Implied FFO >1890 1188 - 1848 739.2 - 1188 449 - 739 264 - 448.8 Implied EBITDA >2230 1402 - 2181 872 - 1402 530 - 872 312 - 530 Implied Debt/EBITDA <1.21 1.93 - 1.24 3.1 - 1.93 5.1 - 3.1 8.67 - 5.1 RCF/Debt Metric Implied FFO >1431 945 - 1431 621 - 945 405 - 621 270 - 405 Implied EBITDA >1689 1115 - 1689 733 - 1115 478 - 733 319 - 478 Implied Debt/EBITDA <1.6 2.42 - 1.6 3.68 - 2.42 5.65 - 3.68 8.47 - 5.65 FCF/Debt Metric Implied FFO >1731 921 - 1704 651 - 921 381 - 651 -24 - 381 Implied EBITDA >2043 1087 - 2011 768 - 1087 450 - 768 -28 - 450 Implied Debt/EBITDA <1.32 2.48 - 1.34 3.51 - 2.48 6.01 - 3.51 -95.34 - 6.01

Tightest Baa ratio

15 Setting Risk Appetite A Worked Example Continued

• On this data the FFO/Debt metric implies to lowest, and most challenging, Debt/EBITDA ratio • Given interest and dividend assumptions, meeting this metric will also deliver performance consistent with at least a Baa rating for the other metrics

• Target can be set to reflect a specific sub-rating within the Metric Baa overall Baa (e.g. Baa1 or Baa2) Max. Debt/EBITDA Ratio Calculated Midpoint 4.10 • Using the midpoint of the metrics range (hence, broadly Rounded ratio applied 4.00 Baa2), Debt and EBITDA targets may be derived as follows: Min. EBITDA (Given debt) 675 Max. Debt (Given EBITDA) 3,200 • Which can then be compared with the budget:

€ Mill Loss from Budget EBITDA

800

675

Performance Minimum

Budget

125

MaxLoss

125

16 Setting Risk Appetite Setting the Confidence Level

• Having established the Maximum (acceptable) Loss, the next 50% step is to associate this loss with a confidence level 80% • Rating agencies will typically: – Apply 3 years historic data in their credit assessments; and

– Make some allowance for occasional underperformance of 1 target financial ratios. 125 • As a rule of thumb, financial ratios need to be on target in at 2

least in 2 out of the previous 3 years to avoid downgrading. 1 Budget EBITDA

• In practice, the BoD is likely to want some additional buffer: Risk Appetite defined at 80% (maximum 2 – For example, the BoD might want to avoid under- acceptable loss in 4 out of 5 years) performing the financial strength metrics 4 out of 5 years; Loss from Budget EBITDA – Hence, the confidence level is 80%. • In this manner, a quantitative measure of Risk Appetite can be derived which expresses the maximum loss (from current budget EBITDA) the BoD will accept in 4 out of 5 years.

17 Determining Group Level Risk Capital Converting Appetite to Risk Capital

• Risk Capital and operational limits (i.e. VaR) are typically set at 95% or 99% confidence • Assuming a normal distribution, losses at 95% and 99% confidence may be derived from the numeric expression of Risk Appetite at 80%: – The losses attributed to 80%, 95% and 99% confidence levels are internally consistent; – They simply measure different points on the (same) EBITDA loss distribution • Continuing the worked example below, the maximum losses at 95% and 99% confidence are consistent with a €125 Mill loss at 80% (neither more or less conservative)

50% 95% Assuming Normal EBITDA Distribution 80% 99% Metric Confidence € Million 1 Budget EBITDA Risk Appetite 80% 125 95% Risk Capital 95% 244 Risk Appetite defined at 80% (maximum 2 acceptable loss in 4 out of 5 years) 99% Risk Capital 99% 346

Risk Capital at 95% consistent with Risk

1 3 Appetite.

125

244 Risk Capital at 99% consistent with Risk

2 346 4 Appetite. 3 Loss from Budget EBITDA 4

18 Allocation and Limits

• The total risk capital available at group level provides the anchor for the limits and controls deployed within the operational business • All risk limits should be derived and explicitly linked to the total Risk Capital taking account of offsets and diversification benefits across the book-structure • Coming up with correlations for the first tier of allocation particularly challenging as this tier necessarily rely on some fairly broad brush assumptions:

Group Level 1

Networks Generation Supply Market Credit FX & Int Level 2

• Level 2 buckets (e.g. market risk) may be supported by well-developed book structures: Market Level 2 • Correlations used in top-down allocation must be consistent with bottom-up consolidation Portfolio Asset Trading Prop Trading Prompt Level 3 • For market risk, should reflect correlation Region 1 Region 1 Region 1 Region 1 matrix in ETRM system Level 4 Region 2 Region 2 Region 2 Region 2

19 Allocation and Limits The Worked Example Again

• Adding some simplistic and invented correlation assumptions to the worked example, the allocation of the €244 Million in Risk capital (at 95% confidence) could look like this:

Group Reserve 244 32

Allocated Capital 212

Networks Generation Supply Market Credit FX & Int Simple Sum 405 30 80 50 130 75 40 Weigthed Sum 212

Market 130

Portfolio Mgt Asset Trading Prop Trading Prompt Simple Sum 163 50 90 12 11 Weigthed Sum 130

Region 1 Region 1 Region 1 Region 1 Simple Sum: 40.1 66.0 10.0 7.8 Region 1 124 Region 2 79 Region 2 Region 2 Region 2 Region 2 Total 203 21.4 47.0 5.0 6.0 Weigthed Sum 163

20 Risk Capital Measurement and Budgeting Risk Triangle

• Financial Risks are “transformable”: Market – Market Risk can be reduced by Risk hedging. This creates Credit Risk, as the effectiveness of the hedge + - - + depends on the counterparty honouring the contract. – Credit Risk can be reduced by exchange of collateral. This creates Cash Liquidity Risk, as - + sufficient short-term cash + - liquidity must be available in the firm to support margin calls. Cash - + Credit Liquidity + - Risk – Unwinding the hedge eliminates Risk the Cash Liquidity Risk but re- introduces Market Risk. • All risk categories must be considered in the Risk Capital framework

22 Risk Allocation and Risk Consumption

1. For each business division/ activity (e.g. generation, origination, etc.) 2. For each risk category (e.g. market risk, credit risk, etc.)

Bottom up Top down

Test consumption Estimate demand of risk capital Allocate available Set risk limits for risk capital as against risk capital to each (consistent with part of annual operational limits business line and metric) in line with budget cycle on a (e.g. daily) activity demand basis

Common risk metrics assure consistency between 1. capital budgeting (strategic) ; 2. risk limit testing (operational)

23 Overview of Risk Metrics

Cash Liquidity Operational Market Risk Credit Risk Risk Risk

Open Price Risk Profile Risk Default Risk

Value at Risk Earnings at Risk Credit VaR

• Seek to calculate the 95th percentile of the P&L distribution for each risk category • Various standard numerical methodologies in the industry

24 Market Risk Portfolio Decomposition

• All VaR measures assume open positions can be closed over a defined holding period: – VaR should only be used for positions which can be controlled on this basis • However, energy portfolios contain: – Physical (delivery) positions; and – Volumetric uncertainty which cannot be approximated by financial options • Applying VaR to positions which cannot be closed ahead of delivery will understate risk • Many companies therefore decomposing their portfolio into: - Tradable (proxy) positions which can be closed ahead of time and hence be controlled and measured using VaR; and - Residual positions and uncertainty which exists close to and at delivery which requires a measure of spot and balancing risks

25 Market Risk Value at Risk

• Value at Risk (VaR) is the most common measure of portfolio market risk in use today. • VaR makes a statement of the following form: “I expect the one-day change in value of the portfolio resulting from market prices movements will be better than a loss of $X on 19 days out of 20” • $X is the Value at Risk (in fact, the 1-day, 95% Value at Risk) • The VaR is the value change which divides the probability distribution into two sections: - Losses greater than the VaR - Losses smaller than the VaR (and profits)

26 Market Risk Residual (Delivery) Risks

• While the residual positions often are relatively small in volumetric terms, they can embed substantial uncertainty as a result of: – Uncontrollable factors such as customers under full supply contracts and plant reliability (or lack therefore); and – Controllable factors such as the optimisation of mid-merit and peaking plant, storage and other flexible assets and contractual positions. • While there is no general industry standard measures of spot and prompt risks, such measures are often know as “Profit-at-Risk” (PaR): • The central assumption in Profit-at-Risk (PaR) is the exact opposite of VaR: – PaR assumes positions cannot be closed out ahead of time and that they therefore are held to delivery; – Open positions are assumed to be realised (in the case of financial contracts, cashed out) at spot prices prevailing at that time.

27 Market Risk Residual (Delivery) Risks Continued

• PaR measures are typically computed using some scenario based simulation model :

Pn Likelihood Pj

P1 Year 1 Year 2 Year 3

V1 Income (P&L) V j Expected PaR (average) Vn

Year 1 Year 2 Year 3 • While the computation of PaR is very simple for a given set of scenarios: – Developing linked scenarios of spot prices and residual volumes may extend to sophisticated stochastic modelling; – May include (quasi) optimisation against each price path using the operational optimisation tools.

28 Credit Risk Credit VaR

• Credit VaR is an industry standard methodology to measure portfolio credit default losses • For a bond portfolio, it is also common to consider credit gains, but for our energy portfolio we assume only losses – Trading exposure – Supply imbalances – Warranties on equipment • Numerical methodology depends on many • For household customers and SMEs, simulations of price evolution of underlying suggest a “bad debt” charge based on market products experience or modelling • Portfolio credit exposures per counterparty depend on netting rules and posted collateral • Loss modelling further depends on simulation of defaults (based on default probabilities) • Calculation intensive !

29 Consistency across the Metrics

• Profit at Risk and Credit VaR are normally calculated annualised metrics – Profit at Risk – distribution of short-term results over 1 year – Credit VaR – distribution of credit loss over 1 year

• In contrast, typical horizons for VaR are 1-day or 10-days – By definition, positions are tradable blocks and can be closed – “Stop-loss” policies: unlikely to hold a consistently money-losing position for a year without changing the strategy – Positions are actively traded and dynamic

• Need to scale VaR metric to be consistent with annual business planning process – Assume static position, use “square root of time rule” • 16 * 1-day VaR, or 5 * 10-day VaR – Basle II requires regulatory capital for market risk of 3 to 4 times the 10-day VaR

30 Bottom up Allocation

• Having defined our consistent risk metrics, we then survey requests for Risk Capital • Our Trading area manages all commodity market risk for the Group. Suppose we receive the following requests:

Our top-down allocation Market 130

Our bottom-up Portfolio Mgt Asset Trading Prop Trading Prompt Simple Sum 248.5 request 80 135.3 22.2 11 Weigthed Sum 202

Region 1 Region 1 Region 1 Region 1 Simple Sum: 60.5 90.3 12.1 7.8 Region 1 171 Region 2 142 Region 2 Region 2 Region 2 Region 2 Total 313 39.3 80.7 15.8 6.0 Weigthed Sum 249

31 Allocation and Limits The Worked Example Again

• Some work to reconcile the bottom- Market Top-down allocation 130 up requests • Risks vary to the degree to which Portfolio Mgt Asset Trading Prop Trading Prompt Simple Sum 163 they are discretionary 50 90 12 11 Weigthed Sum 130 – Difficult to close out profile risk Region 1 Region 1 Region 1 Region 1 Simple Sum: in advance 40.1 66.0 10.0 7.8 Region 1 124 – Sometimes possible to mitigate Region 2 79 some portfolio credit risks (e.g. Region 2 Region 2 Region 2 Region 2 Total 203 21.4 47.0 5.0 6.0 Weigthed Sum 163 margining) – Prop trading risks are fully Market discretionary 130 Bottom-up request • Decisions depend on:

Portfolio Mgt Asset Trading Prop Trading Prompt Simple Sum 248.5 – Expected return of each activity 80 135.3 22.2 11 Weigthed Sum 202 – Targets and objectives set by management Region 1 Region 1 Region 1 Region 1 Simple Sum: 60.5 90.3 12.1 7.8 Region 1 171 • If bottom-up request is below top- Region 2 142 down allocation, possibility to Region 2 Region 2 Region 2 Region 2 Total 313 39.3 80.7 15.8 6.0 Weigthed Sum 249 restructure balance sheet 32

Operational Risk

• Generally, not common to request/ allocate a specific numerical budget for Operational Risks – Unlike market and credit risks, businesses typically have little tolerance for operational risks such as data loss, equipment failure, etc. • Difficult to quantify (few data on which to calibrate models) – Actuarial approaches based on common industry data – Historical operational losses within the organisation • Nonetheless, operational risks do consume risk capital • Possible solutions: – Haircut on Risk Capital at Group level to account for anticipated operational losses – Risk charging (see below) to divisions based on historical operational losses

33 Liquidity Risks

Collateral Risk profile • Market, credit and Operational risks impact the P&L and consume risk capital

• Margining “only” impacts liquid funds temporarily until Inflow collateral is returned, but running of funds is not an option • Essential that the control framework incorporates control

and measurement of margining induced cashflow risks Outflow Early Warning • Actual flows not an indicator of likelihood of adverse future Trigger outcomes (its too late once cash is out the door) Current Time position • Needs to be supplemented with forward looking:

Actual  Baseline forecast of collateral; and Forecast  A measure of the uncertainty (risk) around this forecast Range of future outcomes as a function of market price movements. • Ideally using price assumptions and scenarios consistent with those deployed in measuring market and credit risk

34 Risk Capital Charging Introduction Why Bother?

• Beyond working capital requirements, companies maintain balance sheet contingencies cover cashflow uncertainty from: – Market, credit, and operational risks; as well as – Trading on margined terms (potentially increasing in importance in light of EMIR regulation) • Such contingencies are typically held in highly liquid funds: – Earning very little interest; – Tying up capital which could be deployed to support core business activities • Supporting the business with Risk Capital and liquidity imposes real costs, which if ignored may lead to: – Misallocation and sub-optimal use of scarce capital resources – False assessment of arbitrage opportunities and poor trading decisions – Pricing decisions that fail to take account of all true variable transaction costs • Many European utilities have therefore introduced risk charging in recent years

36 Common Approaches …And their Problems

• A fairly common approach is to: – Cost risk at WACC less the interest that capital contingencies can earn (until needed to cover actual losses); and – Apply this charge directly to the risk limits or measures of risk utilisation at different levels of the book structure. • While such approaches will give the right directional incentives, they sometimes fail to provide a reasonable view of actual (real) costs involved (which generally are overestimated). – Applying a WACC based charge to the total Risk Capital (implicitly) assumes that all such capital requirements need to be backed by ring-fenced reserves; – This does not reflect the typical capital structures and risk provisioning practices actually deployed by utilities and energy companies • Likewise, applying the full charge across different levels of the book structure will fail to account for portfolio diversification benefits: – The gross (simple) sum of risk capital will increase as one moves down the book structure and so will therefore the sum of charges; – For a deep book structure, the degree of over-recovery can be a multiple of the net (real) cost at group level

37 An Alternative Approach

• For most companies, the key objectives for introducing charging are to ensure that: – The cost of supporting trading and commercial decisions with Risk and Cash Collateral Capital is visible, understood and accepted by the business; and – All pricing and position management decisions take account of these cost. • However, for charges to add (real) value to the management of the business, they must be acted upon. In turn means that charges must be: – Viewed and accepted by the business as a justifiable measure of actual costs (as opposed to being based on some notional concept); and – Included in performance reporting and incentives (bonus pool); and • These requirements calls for an alternative approach which: – Links limits and capital requirements with (real) reserves on and off the balance sheet; – Identifies how these reserves impose actual (real) costs on group as a whole; – Recovers these costs through consistent allocation of charges in a manner which is not dependent on the depth of the book structure or the confidence level of the risk metric.

38 Estimating the Cost The make-up of Risk Capital

• Risk Capital is by definition a contingency:

– Often treated as a ring-fenced reserve which is not available

for investment in core assets; and

Capital Working Working –

Assumed to earn (much) less than the Weighted Average Margining Liquidity

Cost of Capital (WACC). Reserves

• While some Risk Capital necessarily needs to supported by liquid

Risk Risk Capital

95%

assets to cover short term impacts;

– Highly uneconomic to ring fence reserves for large

99%

unexpected losses which occur only infrequently; Risk Capital – When such losses do occur capital structure can be modified Assets Core by borrowing against the core asset base.

• In practice, Risk Capital is therefore a mix of: 99%*4 – Actual reserves on the balance sheet (mostly liquid); and – A contingent claim on core assets.

Core Assets Liquid Reserves (net of debt)

Liquid Assets Collateral Limit

Working Capital Risk Capital

39 Estimating the Cost From Risk Capital to (Real) Balance Sheet

• Real ring-fenced capital/liquidity reserves (on or off balance

sheet) are not based on risk capital estimates: Lines  Set to ensure that the business is able to withstand business Credit uncertainty over a limited time-frame; but  Allow the FD time to increase liquidity (modify capital

structure) if needed.

Capital Working Working

• The relationship between the level of liquid reserves and total

Risk Capital is therefore not direct: Liquidity  It is influenced by every factor which impacts liquidity (and

the FD’s experience and judgement); Sheet On Balance

 But will in general terms increase with increased exposure to Reserves cash margining and/or P&L risk factors. • So, the real annual cost attributed to risk and liquidity is: Total Liquidity Working Capital

 Based on the FD’s forecast of the average (liquid) reserves Reserves required for the following year; and  Priced at WACC less forecast short term rates.

40 Estimating the Cost The Worked Example Again

Debt Cost of Liquidity Pre-tax Finance Cost: On Balance Sheet: 10 Year Risk Free Bond 4.0% WACC 7.71% Corp. Bond Premium 1.0% Forecast Overnight Rate 0.50% Cost 5.00% Average Liquidity Cost 7.21% Post-tax Finance Cost: Liquid Reserves 500 € Mill 1) Corporate Tax Rate 28% Group Cost 36 € Mill Cost 3.60% Credit Lines: D/(D+E) 50% Cost 0.75% WACC Contribution 1.80% Secured Lines 250 € Mill Group Cost 2 € Mill Group WACC Post-tax 5.55% Total 38 € Mill Equity Pre-tax 7.71% Risk Premium (Post-tax): Cost and Allocation of Group Liquidty Market Risk Premium 5.0% Liquidity Reserves: Beta 0.70 Working Capital 150 € Mill Cost 3.5% Margining Reserves 100 € Mill Post-tax Equity Cost: Risk Capital 150 € Mill Risk Free Bond (10y) 4.0% Total 400 € Mill Cost 7.5% Cost Allocation (Incl. Credit Lines): E/(D+E) 50% Working Capital 12 € Mill WACC Contribution 3.75% Margining Reserves 8 € Mill Risk Capital 12 € Mill

Total 31 € Mill 41 Allocating the Charge Charge For Limits or Utilisation?

Charge Limits Limit versus Utilisation: • The cost of risk and liquidity arises from the granting of limits. Example A: Example B: Capital Release – Actual reserves must necessarily be able to cover all limits provided to the business; and – The FD and/or Risk Management cannot second guess the extent to which limits will be utilised; Months Months Original Limit (Allocated Capital) • However, to be effective assumes the business has access to Revised Limit relinquish excess limit capacity to release capital (Example B) Monthly Average Utilisation • Does not incentivise risk reduction below the (already paid for) limit Charge Utilisation • Under-recovers real costs where full limit is needed, but only periodically (Example A); • Fails to incentivise release of unused limits as no saving is accredited the business (Example B), but incentivises minimisation of utilisation; • Is more computational demanding.

42 Allocating the Charge Accounting for Portfolio Diversification

• Applying the Group Level charge across the book structure, can over-recover total real costs (very considerably): – Assume the (simple sum) risk capital is €100 Mill and £150 Mill at the first two levels of the book structure and the group charge 5% – Applied to level 2, charges (€7.5 Mill) will over-recover real costs (€5 Mill) by 50% • To avoid over-charging, necessary to reduce the charge at lower levels of the book structure to compensate for the increase in (simple sum) risk capital: – In the above example the charge rate would be reduced to 3.33% (100/150 *5%) • While no longer a single number, charges: – Can still be expressed as a simple schedule of (fixed) percentages for each level of the book structure; and – Calculated as a fixed % * book capital limit Level Charge Group x% Level 1 y%

Level 2 z%

43 Allocating the Charge Taking Account of Risk Diversification Across the Portfolio

• Over-recovery if group charge applied at all levels of the book structure:

Group Limit 244 Charge 4.71% Cost 11.52 Tier 1 Allocation

Networks Generation Supply Market Credit FX/INT Total Recovery Capital 30 80 50 130 75 40 405 Group Level Cost 11.52 Charge 4.71% 4.71% 4.71% 4.71% 4.71% 4.71% 4.71% Charges 19.09 Cost 1.41 3.77 2.36 6.13 3.54 1.89 19.09 Over-recovery 66%

Tier 2 Allocation Market Risk Only PM AT PROP PROMPT Total Recovery (Market Risk Only) Capital 50 90 12 11 163 Market Risk Cost 6.13 Charge 4.71% 4.71% 4.71% 4.71% 4.71% Charges 7.68 Cost 2.36 4.24 0.57 0.52 7.68 Over-recovery 25%

44 Allocating the Charge The Worked Example One Final Time

• Rate adjustment to ensure that only net group costs are recovered:

Group Limit 244 Charge 4.71% Cost 11.52 Tier 1 Allocation

Networks Generation Supply Market Credit FX/INT Total Recovery Capital 30 80 50 130 75 40 405 Group Level Cost 11.52 Charge 2.84% 2.84% 2.84% 2.84% 2.84% 2.84% 2.84% Charges 11.52 Cost 0.85 2.27 1.42 3.70 2.13 1.14 11.52 Over-recovery 0%

Tier 2 Allocation Market Risk Only PM AT PROP PROMPT Total Recovery (Market Risk Only) Capital 50 90 12 11 163 Market Risk Cost 3.70 Charge 2.27% 2.27% 2.27% 2.27% 2.27% Charges 3.70 Cost 1.13 2.04 0.27 0.25 3.70 Over-recovery 0%

45 Contact Us

http://www.esp-consulting.co.uk/

Soren Lautrup Paul Stefiszyn Director (UK) Director (Benelux) Email: [email protected] Email: [email protected] Mobile: +44 (0)7501 720 878 Mobile: +31 6 1130 9750

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