CCRO: Vol 4 of 6, Credit Risk Management Paper by Committee of Chief Risk Officers

VOLUME'4'OF'6 CREDIT'RISK'MANAGEMENT'

Committee'of'Chief'Risk'Of>icers Credit'Risk'Management'Working'Group

November(19,(2002 THE$ COMMITTEE$ OF$ CHIEF$ RISK$ OFFICERS$ (“CCRO”)$ GRANTS$ USERS$ A$ REVOCABLE,$ LIMITED,$ NON: EXCLUSIVE,$ NON:SUBLICENSEABLE,$ NON:TRANSFERABLE$ LICENSE$ TO$ REPRODUCE$ THIS$ DOCUMENT$ SOLELY$ FOR$ INTERNAL,$ NON:COMMERCIAL$ AND$ EDUCATIONAL$ PURPOSES.$ ALL$ OTHER$ RIGHTS$ ARE$ RESERVED$BY$ THE$CCRO.$WITHOUT$ LIMITING$THE$FOREGOING,$THE$ CCRO$DOES$NOT$CONSENT$ TO$THE$ REPRODUCTION$ OF$ANY$ OF$ ITS$ DOCUMENTS$ FOR$PURPOSES$ OF$PUBLIC$ DISTRIBUTION,$ SALE$ OR$ ANY$ OTHER$COMMERCIAL$USAGE.$ATTRIBUTION$TO$THE$CCRO,$AS$THE$ COPYRIGHT$ OWNER,$IS$REQUIRED$IN$ ALL$CASES.

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Table of Contents I INTRODUCTION ....................................................................................................................................1 II CREDIT ALLOCATION AND FINANCIAL RISK ANALYSIS .......................................................3 1.0 Credit Policy ......................................................................................................................................3 2.0 Establishing Credit Limits ...............................................................................................................3 3.0 The Cost of Credit .............................................................................................................................8 III CONTRACTS.........................................................................................................................................9 1.0 Contract Uses and Types ..................................................................................................................9 2.0 Contract/Credit Provisions ...........................................................................................................10 IV MEASUREMENT................................................................................................................................13 1.0 Credit Exposure...............................................................................................................................13 2.0 Distribution of Losses Given Default ..........................................................................................14 3.0 Credit Value at Risk (CVaR) ..........................................................................................................15 4.0 Implications for Credit Charges, Credit Reserves, and Credit Capital ...................................15 5.0 Stress Testing and Scenario Analysis ...........................................................................................16 V MONITORING .....................................................................................................................................17 VI MITIGATION ......................................................................................................................................21 1.0 Types of Risk Mitigation ................................................................................................................21 2.0 Reduction Methods ........................................................................................................................22 3.0 Transfer Methods ............................................................................................................................24 4.0 Multilateral Clearing ......................................................................................................................25

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List of Figures Figure 1. Current Exposure and Potential Exposure ...........................................................................13 Figure 2. Loss Distribution ......................................................................................................................15 Figure 3. Exposure without Multilateral Netting.................................................................................26 Figure 4. Exposure with Multilateral Netting.......................................................................................27 Figure 5. Simulation of Guaranty Exposure for Bilateral and Multilateral Netting........................28 Figure 6. Cumulative Probability Distribution of Exposure Reduction with Multilateral Netting .............................................................................................................................................................28

List of Tables Table 1. Financial Metrics for Establishing Credit Limits .....................................................................5 Table 2. Methods for Managing Credit Risk Exposure........................................................................22

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I INTRODUCTION By participating in energy commodities markets throughout the world, companies are exposed to a variety of market and credit risks. However, each company has developed its own financial reporting practices, risk management techniques, and infrastructure to manage its business. The Committee of Chief Risk Officers (CCRO or the Committee) has been formed in an effort to compile risk management practices surrounding these activities. The Committee is composed of Chief Risk Officers from leading companies that are active in both physical and financial energy trading and marketing. They are committed to opening channels of communication and establishing best practices for risk management in the industry. The impetus behind the formation of the CCRO was the recognition that the merchant energy market has developed to the point where the industry needs to revisit existing methods. We have attempted to provide guidance on new methods and tools to establish a strong foundation for future growth in the industry. We view this as an opportunity to establish industry practices to benefit market participants, investors, and ultimately consumers. The CCRO established working groups to address four key areas – Organizational Independence and Governance, Valuation and Risk Metrics, Credit Risk Management, and Risk Management Disclosures. The Governance Working Group was charged with developing guidance on the control infrastructure for two primary areas: the business processes and the governance over them. The Valuation Working Group was charged with developing methodologies and risk metrics to provide management with meaningful, consistent information about the values and risk exposures inherent in merchant energy operations. The Credit Working Group was charged with developing guidance on credit risk management and efficient use of credit. Finally, the Disclosure Working Group was charged with developing meaningful disclosures that are responsive to stakeholders, such as investors, credit rating agencies, financial analysts, regulatory bodies, other industry associations, and the media, and that provide insight into company and industry performance. In the following white papers, the CCRO presents the results of the first phase (March–October 2002) of our efforts. During this phase, the working groups met regularly to review and discuss participant company practices and studies, as well as feedback from external stakeholders. In presenting these best practices, the CCRO intends to create common nomenclature, methodology, metrics, and processes. These best practices build on and strengthen current industry standards. During our research process, we found that while many companies already followed many of these practices, they were not codified and universally accepted as standards. The CCRO strongly encourages the industry to adopt the best practices outlined in the white papers. We believe that adoption of these practices reduces risk, fosters liquidity, and increases the efficiency of the trading and marketing of energy, which benefits consumers and investors. We expect that these best practices will evolve and further develop through our future investigations and through the efforts and experience of the companies adopting and implementing them. © Copyright 2002, CCRO. All rights reserved.

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Note that the best practices herein are offered as a resource. Their use is voluntary, and no company has agreed to or is required to use them. In addition, they may be modified as appropriate by individual companies, and they do not relieve any company from the need to comply with their legal and professional requirements. For further information on the aims and the objectives of the CCRO (including appropriate use of best practices), please refer to Volume 1 of this set of white papers. The purpose of this document is to present a set of credit risk management best practices for the energy merchant industry. We define credit risk as the cumulative potential nonpayment and nonperformance of counterparties on contracts to buy or deliver energy products and derivatives thereof. Counterparty credit exposure is equal to the sum of all money due (billed or delivered and unbilled) plus the replacement cost of the contracts if positive (netted if appropriate). While these definitions are not unique to energy, the contract structures and credit risk arising from commodity price behaviors are decidedly unique. Energy merchant credit risk management is concerned partly with industrial trade credit (because of the physical commodity business) and also partly with derivative and mark-to-market (MTM) credit risk. This document covers the five key credit risk management functions: •

Credit Allocation and Financial Risk Analysis – This section provides a set of best practices for setting credit policy, for establishing credit limits based on the quantitative and qualitative counterparty analysis, for creating a scoring system to rate portfolios and counterparties, and for assessing the cost of credit associated with a counterparty.

•

Contracts – This section provides a set of best practices related to contractual arrangements used by energy firms. It encompasses a brief description of the financial and physical master contracts as well as a set of credit provisions that energy companies can select to better manage and mitigate credit risk.

•

Measurement – This section provides a set of best practices for measuring the credit risk inherent in the energy business. The discussion extends into the exposure measurement process and credit value at risk (CVaR).

•

Monitoring – This section provides a set of best practices for monitoring an energy firm’s credit risks. The discussion concentrates on the monitoring of counterparty credit quality, credit exposures, contractual arrangements, margining, and exceptions.

•

Mitigation – This section provides a set of best practices for mitigating credit risk and focuses on two general approaches: reduction and transfer. The reduction methods include establishing credit limits, monitoring and collateralizing credit exposures, and using appropriate contractual arrangements (e.g., master netting agreements). The transfer methods concentrate on the transfer of credit risk to the financial markets through the use of financial guarantees, credit insurance, and credit derivatives. This section also covers the concept of clearing energy products, including a set of desired attributes in clearing solutions and descriptions of current providers of clearing solutions.

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II CREDIT ALLOCATION AND FINANCIAL RISK ANALYSIS 1.0 Credit Policy A company establishes credit limits for a counterparty based on its “risk tolerance” as determined and approved by its board of directors and as set out in its credit policy. Thus, the initial step in deciding how to allocate credit is to establish a credit policy. Such a policy should include the following: •

Guidelines for establishing credit limits and allocating credit to counterparties (These guidelines are described at length in Sections III-2.0 and III-3.0.)

•

Guidelines regarding when and how to request credit

•

Guidelines for monitoring trading lines

•

Guidelines on specific types and tenor of transactions allowed

•

Guidelines on segregation of duties between commercial teams and credit teams, up to the chief executive officer (CEO) or board level (See the Governance and Controls White Paper)

•

Guidelines on the levels and allocation of authority, from the credit analyst to the CEO (See the Governance and Controls White Paper)

•

Guidelines for approving exceptions.

2.0 Establishing Credit Limits The establishment of monetary credit limits and tenor limits should weigh the creditworthiness and size of the counterparty along with the strength and type of contract used to document the transaction. Credit lines should be defined in dollars and should consider the accounts receivable and MTM portions as well as tenor. To assist in establishing credit lines, the use of financial ratios or metrics (for examples, see Table 1) will facilitate new counterparty setups and provide guidance for real-time situations where existing counterparty lines have to be adjusted. When establishing credit limits, the credit manager should account for and factor in a counterparty’s specific characteristics. Also, these financial metrics should be considered and adjusted to reflect the current economic environment and trends within given business segments. While neutral to any industry or business segment, Table 1 below is meant to provide an example of key metrics to be used and their variation by credit quality.

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Table 1. Financial Metrics for Establishing Credit Limits Most Recent FYE – S&P_ 100 Financial Ratio Medians AAA A+ ABBB+ BB+ Pretax Interest Coverage (x)

25.5

7.6

3.1 1.2

EBITDA Interest Coverage (x)

36.5

9.4

7.6

Total Debt / EBITDA (x)

0.8

1.8

Long Term Debt / Capital (%)

18.7

Total Debt /Capital (%)

37.8

B+

1.7

(19.2)

5.4

3.4

(5.0)

2.1

3.5

4.5

4.3

42.9

27.9

44.8

46.4

55.4

52.3

30.5

57.9

53.3

65.2

There are universal principles of credit strength that allow credit managers to tailor the standards on which they would grant credit. Among these are company size, industry characteristics and trends, profitability, liquidity, cash flow, interest and fixed-charge coverage, and capital structure. Credit ratings, whether from ratings agencies or internally developed (see “Scoring Model” below), are meant to capture all the universal principles and provide a common basis for expressing the credit strength of the portfolio. As a best practice, however, rather than relying solely on published credit ratings, we believe that credit managers should employ thorough financial analysis in deciding whether to extend or deny unsecured credit. Financial risk analysis is performed to determine the underlying creditworthiness of the counterparty and assess its capacity to perform financial and nonfinancial obligations. This involves taking into account the direct credit risk based on the counterparty’s financial profile and the indirect industry risks. Hence, credit analysis involves assessing the financial condition of the counterparty through the analysis of its underlying financial performance, as exemplified by its financial statements (income statement, balance sheet, statement of cash flow), an analysis of the industry, and an understanding of how subjective factors influence capability to financially perform. The following points should be included in a best practice approach to credit analysis (as discussed above, these should be adjusted to reflect a counterparty’s specific characteristics):

Financial Statement Analysis •

Income Statement Analysis − − − −

•

Historical revenue, costs, and earnings trends Degree of operating leverage, and thus a basic understanding of the fixed and variable cost structure of the counterparty Gross profit, EBIT, and EBITDA margins and trends Coverage ratios, including EBITDA/interest and EBITDA/(principal and interest).

Balance Sheet Analysis − − − −

Asset efficiency ratios Working capital position, including the liquid nature of its current assets and available cash When applicable, the composition and net position of the counterparty’s price risk management assets and liabilities Return on assets (ROA).

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•

Capital Structure and Liquidity Layout − − − − −

•

Assessment of the historical success of the counterparty in tapping the capital markets (debt and equity) Assessment of bank financing in place, terms thereof and the implications this has on the counterparty’s future liquidity requirements and ongoing viability Off-balance-sheet liabilities Funded debt to capital ratio Funded debt to EBITDA.

Cash Flow Analysis − − − −

Operating cash flow and operating cash flow before changes in working capital Investing cash flow, including future capital expenditures (CapEx) requirements Financing cash flow, including changes in debt and dividend requirements Net cash flow and impact on ending cash balance.

Industry Outlook Summary and Peer Group Comparison − − − − − − − −

Counterparty and peer group analysis, industry outlooks (for example Moody’s, Standard and Poor’s, S&P’s Research Insight – Compustat software) Annual reports and Form 10-K, CERA Research, and Internet Summary of recent events relating to the counterparty Merger and acquisition activity Changes in sources of liquidity Significant CapEx or investment activity General business performance updates Equity analysts’ research reports.

Subjective Factors − − − − − − −

Tenure/experience level of management Market share Competitiveness of product lines Ability to manage the business within economic business cycles Size and geographic diversity Product life cycle Risk management policy, internal controls, etc.

Scoring Model These principles and metrics should be used for formulating an internal scoring model to rate counterparties. Scoring models are meant to capture and analyze the financial condition of a company according to specific financial metrics, which are benchmarked against publicly available data (i.e., credit ratings and underlying financial health grouped by industry settings, SIC). Having assigned a rating to the counterparty, the credit manager should be able to risk weight the portfolio and determine exposure concentration within a particular credit category.

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As a best practice, a consistent rating mechanism should be established based on the credit analysis performed according to guidelines given in the previous section and should achieve at least three objectives: •

Assign an internal rating to all counterparties, thus ensuring a consistent risk profile for all credits in conjunction with the credit policy guidelines

•

Adjust the ratings based on the direction, magnitude, and timing of a counterparty’s credit changes. Financial analysis should be performed with some scheduled regularity —at least annually or as circumstances demand to manage the dynamic credit environment

•

Facilitate the establishment of portfolio default probabilities based on the portfolio’s risk weighting. (See the Valuation and Risk Metrics White Paper Section III on Sensitivity Analysis, Scenario Analysis, and Stress Testing.)

As with traditional credit analysis, scoring models should have the flexibility to adapt and take into account counterparty-specific characteristics. A scoring model may include some of the key financial metrics listed below (at the discretion of the credit manager):

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•

Revenues

•

Gross profit

•

EBIT

•

EBITDA

•

Gross profit margin

•

EBIT margin

•

EBITDA margin

•

Current ratio

•

Quick ratio

•

Current portion of long-term debt

•

Total debt

•

Total funded debt (total debt adjusted for leases, off balance sheet debt, mandatorily redeemable preferred).

•

Funded debt to capital

•

Funded debt to EBITDA

•

EBIT to interest

•

EBITDA to interest

•

Funds from operation (FFO)

•

Operating cash flow (OCF)

•

FFO to debt

•

OCF to debt

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The model or process that is adopted for credit risk management should be reviewed by the Risk Oversight Committee or its delegate at least once a year and understood so that it is not simply a “black box.” There are many commercially available rating models. There are also well-regarded consultants in the field, including consulting groups within the rating agencies, who will help a firm build its own credit scoring models.

3.0 The Cost of Credit Economic costs being placed on the business should be evaluated. Credit risk managers should develop measures that reflect these costs and encourage optimization of risk utilization by traders and trading management. Some of the costs are counterparty specific; others apply more generally to the trading business. Energy marketing and trading companies should assess a counterparty “credit charge.” The purpose of this credit charge is to give traders an incentive to trade with stronger counterparties or collect an appropriate risk premium for taking weaker counterparties by creating a transparent cost of dealing. Note that while we view this approach as a best practice, it is not easy to implement, especially in day-to-day trading. The challenges of applying a credit charge to regular trading activities are heightened because the online trading platforms do not include a credit charge for the prices posted on these platforms. Additionally, some trades could qualify as exposure-reducing trades (see discussion in Section VI), thus providing an inherent benefit to the organization. Structured transactions should be priced inclusive of a credit reserve reflective of the credit risk of the transaction. There are a couple of methods for developing these costs. One is to apply historical default rates to the transaction price as a deduction from the value of the transaction. For example, for a particular transaction type and maturity, counterparty A may have a 2% default rate on financial obligations. By multiplying this default rate by the fair value of the transaction, a charge may be assessed. The advantage of this approach is that the credit assessment is directly related to real performance. Unfortunately, historical information may not always be available. Furthermore, this method is tied specifically to financial default, not to performance under the contract generally. Another method is to look at specific counterparty risk premiums in traded bonds or default swaps and apply that risk premium (percentage) to the transaction price. For example, counterparty A may have a one-year credit spread to treasury bills of 30 basis points. A credit assessment can be obtained by multiplying these 30 basis points by the fair value of the transaction. Unfortunately, while this may be the most current market assessment, it may not be directly applicable to a non-rated counterparty. In addition, this approach assumes that the company issuing credit has a rating of AAA or similar, which could result in overcharging counterparties. This method also assumes that the bond market is efficient, and that the spread relative to risk-free rates is highly correlated to the cost of credit over the life of the transaction.

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III CONTRACTS 1.0 Contract Uses and Types Although a thorough, accurate, and well-constructed credit analysis can provide the credit department with sufficient comfort to assign an unsecured credit limit, the counterparties may give up some or all of their rights if the proper contractual arrangements are not fully executed. As a best practice, trading should not commence before having fully executed contracts. Companies should execute a master agreement containing netting, set-off, cross-default, closeout, and margining provisions governing all financial transactions and a master agreement governing all physical transactions with respect to the same commodity. There are a number of different standard product contracts. The use of these standard product contracts creates a more efficient market, lowers the barrier for a broader group of participants, and provides more standard terms. Master agreements that are widely adopted and well evolved include: •

International Swap Derivatives Association Inc. ― Master Agreement (ISDA)

•

Edison Electric Institute ― Master Purchase & Sale Agreement (EEI)

•

Western Systems Power Pool – Western Systems Power Pool Agreement (WSPP)

•

North American Energy Standards Board ― Base Contract for Sale and Purchase of Natural Gas (NAESB)

•

Gas Industry Standards Board ― Base Contract for Short-Term Sale and Purchase of Natural Gas (GISB)

The ISDA and the EEI are the recommended contract structures for financial trading (of any commodity) and power, respectively, because of their widespread use and acceptance among market participants. Also, for power, the WSPP is another widely used contract that incorporates some credit protection measures, although it is not as clear and concise as the EEI. For gas, the NAESB, which contains netting provisions and is a newer product, is a stronger contract than the base GISB, but the GISB’s evolution within many companies (special provisions, added language, etc.) can make it comparable to the NAESB. Margining is a preferred method of securing credit risks. The ISDA and the EEI have developed credit support annexes that provide robust and well-defined procedures for the exchange of collateral. The use of the credit support annex under the ISDA and the EEI is considered a best practice to gain the ability to manage credit quality. While the base EEI has margining provisions, they do not clearly define exposure, margining rights or the transfer, holding, use, or return of collateral. Therefore, the recommended approach is to use the EEI Credit Support Annex. The WSPP is in the process of developing credit terms similar to the EEI Credit Support Annex. The GISB contract is commonly used for short-term physical gas sales. Although the NAESB contract was developed to govern both short-term and long-term gas sales, it does not contain collateral thresholds provisions. Many companies have added margining provisions to these © Copyright 2002, CCRO. All rights reserved.

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form contracts and any desire to margin under the GISB or NAESB would have to be appropriately documented. Should trading begin before the relationship has been fully documented, a long-form confirmation must be used. Long-form confirmations should include the majority of the credit terms necessary to actively manage credit risks (see Section 2.0 for discussion of provisions). One of the limitations of long-form confirmations is that the counterparty signs the confirmation after the trade is done. Thus, the risk exists that the credit provisions associated with the trade are materially changed by the counterparty and may not be enforceable should the confirmation not be executed. In addition, to achieve desired netting and close-out provisions, the appropriate language must be incorporated within the long-form confirmation and/or a separate document that captures the appropriate language. While the legal department should be responsible for the overall format and content (excluding credit terms) of long-form confirmations, the credit department should have the ultimate authority for approving their use.

2.0 Contract/Credit Provisions In documenting any transaction, a best practice is to carefully consider each of the following points. •

Is MTM exposure marginable?

•

Are delivered physical products marginable?

•

What types of collateral are acceptable?

•

How is posted margin managed? Commingled funds or segregated?

•

Other rules and procedures for margining (i.e., timing; dispute resolution)?

•

What type of netting provisions? Monthly payment netting, close-out netting, or both?

•

Are termination rights defined? Termination payment calculation?

Credit Thresholds Contractual arrangements should allow for margining of both MTM and accounts receivable (delivered and billed, and delivered and unbilled). Physical gas agreements should incorporate credit terms and provisions similar to the ISDA and/or the EEI. The language used to set a dynamic credit threshold based upon current credit condition can be classified into three groups: financial covenants and material adverse change (MAC) clauses, rating triggers, and adequate assurance clauses. Financial Covenants: Financial covenants include provisions that require counterparties to maintain certain financial ratios (such as total debt to total capital, EBIT/interest coverage, or FFO/total debt) in order to maintain unsecured credit. While these clauses provide objective criteria that can be defined and measured on a regular basis, it is exceedingly difficult to define all financial covenants that will capture each counterparty’s stress scenario. Moreover, these financial measures are delayed by financial reporting and provide little relief in situations involving restatement of financial results. (See the Valuation and Risk Metrics White Paper Section III on Sensitivity Analysis, Scenario Analysis, and Stress Testing.) © Copyright 2002, CCRO. All rights reserved.

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Rating Triggers: Rating triggers provide an objective measure of creditworthiness that can be used to decrease credit thresholds as counterparty ratings decrease. Ratings established by S&P, Moody’s, and Fitch can be used as a proxy for credit quality and can be embedded within the contract, allowing both parties to establish the potential of margin during the term of the contract. However, both Moody’s and S&P have commented negatively on the use of rating triggers or an event that would create a trigger. The agencies have focused on the potential liquidity drain as a company’s rating decreases. To reduce the sensitivity of a rating agency’s actions, energy companies should have the rating triggers apply only when two out of three rating agencies (if appropriate and if split ratings are disregarded) downgrade their credit ratings below a certain level. In some cases, however, downgrade events have taken place after defaults have already occurred and many parties relying on rating triggers to gain access to additional collateral were unable to do so. Adequate Assurances: Adequate assurance is a third alternative risk managers can use to manage their risk. Adequate assurance is a subjective measure that generally provides that if one party has reasonably determined that the other party may be unable to perform its obligations under the agreement(s) between the parties, the insecure party may ask its counterparty for some assurance that it will be able to perform. Adequate assurance could provide the risk manager with flexibility and the opportunity to use his/her judgment rather than defer credit decisions to the rating agencies. By its subjective nature, calls for adequate assurances can be disputed by the counterparty. However, if the call is reasonable, the failure of the counterparty to provide assurances will allow the requesting party to take appropriate actions to protect its position. There is no contractual language that will provide protection for every credit situation. However, as a best practice, one of the three options provided above or some combination thereof based on one’s own particular credit profile, risk tolerance, and market position should be considered.

Additional Provisions We believe that contractual arrangements should clearly define each party’s rights and remedies. From a credit standpoint, typical contract provisions include calculations of termination payments and cross-default or cross-acceleration clauses. The “termination payment” is calculated as follows: Begin with the termination value of transactions that have future delivery dates or maturities; add the net amount of all other payments owed but not yet paid between the parties, whether or not such amounts are then due, for performance already provided pursuant to any and all transactions conducted under this agreement; subtract the amount of any performance assurance then held by the requesting party. The termination value itself is determined by calculating the market value of the remaining transactions using relevant market prices for the remaining term, either quoted by bona fide third parties or reasonably expected to be available in the market under a replacement contract for each such transaction. It is a best practice to include adequate cross-default or cross-acceleration clauses for an added measure of credit protection. These clauses are meant to trigger a request for collateral and/or a © Copyright 2002, CCRO. All rights reserved.

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termination event. Thus if a counterparty has a financial problem, as exemplified by a default to a third party, this clause could provide the nondefaulting party sufficient time to reduce or eliminate potential losses. Most cross-default or cross-acceleration provisions are tied to indebtedness for borrowed money or defaults under other trading agreements, although this should be carefully evaluated for each counterparty.

Master Netting Agreements Another significant means of mitigating credit risks is through the execution of master netting agreements, which govern all transactions under the various financial and physical master agreements selected by the counterparties. Master netting agreements provide for close-out netting across products and a single termination payment upon close-out of the underlying transactions. Some master netting agreements also provide for cross-product margining by including credit support terms that net the exposures across all underlying financial and physical master agreements. EEI has, in concert with the industry, developed a standard master netting agreement. This agreement provides for single-entity cross-product netting, as well as cross-product margining through an accompanying credit support annex. The EEI master netting agreement was formally introduced to the industry in the third quarter of 2002. In addition, EEI also developed a standard master netting agreement that provides for close-out set-off only without margining. Both of these documents were accompanied by a landscape describing some of the legal issues that users and their counsel should consider when structuring such arrangements. The industry continues to discuss a broader application to allow for cross-product netting across affiliate groups. (See further discussion in Section VI.) Some legal issues raised by the use of master netting agreements remain untested, but many of the same benefits can be achieved through careful selection of cross-default, cross-acceleration, setoff, and collateral provisions in the separate master agreements discussed above. Currently, structured product transactions tend to be documented separately from standard product trading, even if the commodity or product could be transacted under one of the other master contracts already discussed. The reasons for this include the term, length, size, and purpose of the transaction. All the same points outlined above remain critical in constructing the credit terms for a structured transaction. We recommend using one of the contracts we have discussed, making the product master agreement transaction specific for the structured transaction. If other documentation is used, it would be beneficial to use terms, rules, and procedures with respect to credit that are generally incorporated in industry standard master contracts.

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IV MEASUREMENT In this section, we describe a framework that credit managers can use to think about various credit risk metrics being discussed in the industry today, including potential exposure, loss distributions, and Credit Value at Risk (CVaR). The specific implementation and modeling of the components will not be prescribed here, but left to the discretion of individual companies, given that companies may have different analytical capabilities and that techniques for modeling energy credit risk are still evolving. Best practice includes the routine application of potential exposure and loss distribution analysis, both for the trading portfolio and for large structured transactions, to adequately communicate working capital needs and balance sheet commitments associated with trading, marketing, and hedging to the company’s senior leadership and board of directors.

1.0 Credit Exposure The starting point for measuring risk in the credit portfolio is identifying credit exposure. Two types of exposure need to be measured: current exposure, and potential exposure. Current exposure includes both billed and unbilled receivables for product that has already been delivered, as well as MTM exposure for products yet to be delivered. If the companies have netting agreements in place, receivables would be netted against payables, both billed and unbilled, for product that has already been delivered. In this context, “product” could mean either the actual physical commodity or a cash payment tied to some market measure of the underlying commodity’s value. Potential exposure measures the range of values that current exposure could take over a given time horizon as a result of price and/or volumetric uncertainty. The relationship between current and potential exposure is described graphically in Figure 1, which shows a frequency distribution of the credit exposure. Figure 1. Current Exposure and Potential Exposure

Figure 1 illustrates a case where current exposure is positive. A positive exposure means that the entity is a net creditor, whereas a negative exposure means that the entity is a net debtor. The graph highlights the fact that over the given time horizon, exposure can increase or decrease © Copyright 2002, CCRO. All rights reserved.

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relative to current exposure. Note that for assessing credit risk, one would only be interested in the positive exposures.

Calculating Potential Exposure Potential exposure can be calculated at the transaction, counterparty, or portfolio level. The time horizon over which potential exposure is calculated depends on the situation being assessed. For example, potential exposure for a specific deal could be simulated to delivery. At the portfolio level, some companies calculate potential exposure over a one-year period. Ideally, potential exposure should be calculated using a simulation model that re-values the credit portfolio for each outcome. The most sophisticated simulation models would capture price and load uncertainty and accommodate cross-commodity and inter-temporal correlations. Note that simulation models used to calculate VaR can also be used to calculate potential exposure. Interestingly, one can view market risk as being captured by downside VaR while viewing credit risk as being reflected by upside VaR. However, simulating credit exposure would generally be more involved since the calculations need to account for the drop-off in positions that mature during the period being analyzed. To the extent that companies do not have access to simulation models, potential exposure can be approximated using parametric VaR calculated for each counterparty (i.e., counterparty VaR). Counterparty VaR measures how MTM exposure to specific counterparties can change for a given time horizon and confidence level. Counterparty VaR can be converted to potential exposure by accounting for netting and other adjustments described above. This approximation is meaningful when looking at potential exposure to each counterparty independently of the portfolio. Note, however, that adding the potential exposure at each percentile across all counterparties will overstate the portfolioâ&#x20AC;&#x2122;s true potential exposure, since counterparty exposures are not likely to vary in the same direction at the same time.

2.0 Distribution of Losses Given Default A loss distribution captures the risk that a company could lose money as a result of counterparty default. Calculating a loss distribution requires information on default probabilities, potential exposure, and recovery rates. A default probability indicates the likelihood that a counterparty will fail over a given time horizon. To arrive at a loss distribution, a default probability must first be assigned to each counterparty. This can be done using proprietary models, commercially available models, or published data from rating agencies. Ideally, default probabilities should reflect the possibility of correlated defaults and credit ratings migration. Accounting for migration is especially important when performing the analysis for long time horizons. A loss distribution can be calculated either at the counterparty or portfolio level. To generate a loss distribution, one can jointly simulate potential exposure and default incidence based on the assigned default probabilities. Note that only positive exposures need to be considered insofar as negative exposures do not lead to losses when counterparties default. Moreover, losses need to be adjusted for any recovery that can be expected in the event of counterparty default.

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Although it is a best practice, simulating the loss distribution can present a formidable challenge. Given this, some companies may elect to use simpler but cruder approximations in describing potential credit losses at the counterparty level in cases where more sophisticated analysis is not possible or not warranted.

3.0 Credit Value at Risk (CVaR) Graphically, the loss distribution can be illustrated as shown in Figure 2.

Figure 2. Loss Distribution

In the above diagram, 95% of the calculated losses are less than the P95 loss whereas the weighted average of all calculated losses is given by the expected loss. The unexpected loss, or CVaR, is the difference between the potential loss at a given confidence level (95% in this case) and the expected loss over a given time horizon (for which potential exposure was calculated). The above definition of CVaR is consistent with that detailed in Jorionâ&#x20AC;&#x2122;s Financial Risk Manager Handbook 2001-2002. However, there is currently no consensus in the industry as to an official definition of CVaR. For example, CVaR is sometimes defined as the entire P95 loss, without regard to the expected loss. In still other cases, the term CVaR has been used to describe the oneday change at some confidence level in the expected loss of the portfolio, as opposed to the simulated actual losses over a longer time horizon. Adding to the lack of consensus around the definition of CVaR, there has been some confusion about the appropriateness of CVaR as an indicator of credit risk in the way that VaR is used as an indicator of market risk. In future work, the CCRO will endeavor to clarify the definition, calculation, and uses of CVaR as a credit risk metric.

4.0 Implications for Credit Charges, Credit Reserves, and Credit Capital Credit Charges Ideally, risk originating units should be assessed a credit charge that reflects the cost of managing the credit risk of the transaction or portfolio. (See discussion on Cost of Credit in ÂŠ Copyright 2002, CCRO. All rights reserved.

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Section III.) If a market-based cost of credit is not available, the credit charge could be set based on the expected loss and the CVaR.

Credit Reserves If the cost of credit is not already captured in the MTM process, credit reserves should be taken to reflect the impact of credit risk on the fair value of the position. Ideally, the reserves should reflect the cost of laying off the credit risk to the market. When market indications for this purpose are not available, credit reserves can be set based on the current and potential credit exposure, taking into account netting arrangements, collateral, and estimated default experience based on the credit ratings of counterparties.

Credit Capital To address the risk that losses could significantly exceed the expected loss in case of default, the company must allocate enough credit capital to absorb unexpected portfolio credit losses at some high confidence level (the confidence level used could be set as a function of the credit rating that the company wishes to maintain). A significant area of future work for the CCRO will be to describe a framework that can help industry participants address capital adequacy issues.

5.0 Stress Testing and Scenario Analysis 1 A thorough program for measuring credit risk should include stress testing to measure the impact that extreme events or combinations of events would be expected to have if they occurred. The factors to be stressed are market factors, counterparty factors, and the correlations among market factors and counterparties. The risk manager should identify (1) extreme market events that give rise to extreme credit exposures for the portfolio as a whole, (2) individual counterparties where a large exposure may become a large risk in the event of adverse developments for that counterparty, and (3) combinations of events that, although currently uncorrelated, could become correlated and thereby create large risks. While these extreme scenarios may have a very small probability of occurrence, the intent of stress testing is to identify their impact if they do occur and confirm the survivability of the company in the event of such rare occurrences. More important, tracking the stress sensitivity to specific troubled individual counterparties as described in (2) provides valuable guidance on strategies to mitigate exposure.

1 See

the Valuation and Risk Metrics White Paper Section III on Sensitivity Analysis, Scenario Analysis, and Stress Testing.

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V MONITORING Integral to the success of managing counterparty risk is a comprehensive set of procedures and information systems to monitor counterparty credits across various portfolios. These procedures should define criteria for identifying and reporting potential problem credits and transactions to ensure that they are subject to more frequent monitoring as well as possible corrective action, reclassification, and allocation of appropriate reserves. (See the Governance and Controls White Paper for information on segregation of duties.) Key monitoring aspects of an integrated credit risk management system follow. •

Allow for monitoring to occur at various levels within the organization – management, operational, and analyst

•

Ensure that the company understands the current financial condition of the counterparty

•

Monitor compliance with existing contractual provisions

•

Identify contractual payment delinquencies and classify potential problem credits on a timely basis

•

Direct problems for corrective action

•

Monitor the composition and quality of the credit portfolio

•

Identify areas of concentration

•

Determine the adequacy of reserves (Note that there are a number of approaches for determining adequate reserves. The Credit department should work with the Accounting department to determine the right approach.)

•

Capture current and potential counterparty exposures that are large relative to allocated capital resources, including large exposures with low probabilities of default and smaller exposures with high probabilities of default

•

Identify correlated risks, including correlated market and counterparty credit risks

•

Identify uncorrelated risks that may become large if they become correlated under stressed market conditions.

For the various components of credit administration to function appropriately, senior management must understand and demonstrate that it recognizes the importance of monitoring and controlling credit risk and must allow proper systems, policies, and procedures to be put into place. The complexity of many credit exposures requires utilizing an approach based on large risk reporting, not just large exposure reporting. Large exposures might include exposures that are large in absolute size, large relative to their applicable limits, large within their rating categories or large in terms of economic capital usage (large risks). Exposure reporting and monitoring should cover all activities with a counterparty. At a minimum, accounts receivable, MTM, and accounts payable should be monitored on a daily basis. As a first step, companies should focus on implementing systems and processes that allow cost-free mitigation techniques, i.e., netting. Individual companies should assess the cost © Copyright 2002, CCRO. All rights reserved.

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benefit associated with intraday monitoring. As a best practice, use of next-day counterparty and position information should be the minimum standard for monitoring credit risk. The following is a comprehensive list of sample reports to serve as a guide to best practice.

Contract Database Integral to the success of credit risk mitigation is the ability to exercise contractual provisions in a timely manner. Several reports to consider in monitoring and maintaining the life cycle of the documentation process include: •

Unexecuted/under negotiation/missing contracts and addendums by counterparty, product, business unit, commodity, contract type

•

Document exceptions aging, document pending aging, and expiring document reports

•

Inactive contracts (number, dollar amount)

•

Transaction exception report

•

Counterparties with netting/set-off rights

•

Listing of exceptions to minimum contract standards for key attributes

The scanning of the actual executed contracts is an additional element of the contracts database that is necessary to manage credit risk in the most efficient manner.

Margin Management The financial implications associated with margining require organizations to use a proactive approach to tracking and managing the various components of a collateral desk. •

Collateral held by counterparty: relationship, type, and expiration

•

Active counterparties with collateral deficiency

•

Letter of credit inventory

•

Parent guarantee inventory

•

Payment/settlement, margin fails, and unsatisfied MAC demands

Limits Management Once limits are established, it is necessary to monitor, on a regular basis, the position limits established for each counterparty. •

Counterparty detail report: exposure, limit and collateral analysis

•

Exposure analysis by counterparty family, tenor

•

Exposure trend analysis and limit concentrations (by industry, region, ultimate parent, commodity product, risk grade)

•

Aging of receivables

•

Deals approved with exceptions

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•

New counterparty/limit approved: last 30 days by business by SIC, limit amount and risk rating

•

Watch list/counterparties within X percentage or dollar amount of established limits

•

Limit violations/excesses

•

Trending of limits exceptions by exposure and units (number of deals and counterparties) based on business, commodity, SIC, etc.

•

Trends: Excess limit by risk rating

•

Trading halted

Common Counterparty A fundamental cornerstone of credit risk management is the ability to capture accurate and reliable counterparty hierarchy information (parent/subsidiary relationships). •

Counterparty data inventory/maintenance report by ultimate parent

•

Counterparty agreement inventory

•

Counterparty exception report: Incomplete identifying information, number of days from previous review

Analytical Tools/Reserves General reports used to manage key performance indictors include: •

Credit memorandum (the basis for the risk rating and limit assigned)

•

Financial statement exception report

•

Risk rating/change and credit score exception reports

•

Estimated default frequency (EDF) change summary

•

Reserve and capital adequacy

Credit Infrastructure •

Deals pending approval

•

Deals approved, not documented

•

Deals approved/declined by product, analyst, etc.

•

Upcoming periodic reviews to be scheduled (by business and counterparty)

•

Aging of overdue periodic reviews (by business and counterparty)

Other Reporting •

Tracking and aggregation reporting for indirect exposures

•

Non-liquid collateral tracking, reporting and expiration management

•

“What If” analysis for tenor analyses at counterparty and portfolio levels

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•

New counterparties/new limits since last report

•

Watch list: current events monitoring

•

ROA/ROE trends

•

Transactions by legal jurisdiction

Monitoring and reporting credit risk relates directly back to the risk analysis process and to strategic decision-making. With knowledge of counterparty and transactional information, an analyst can react to changes in counterparties’ creditworthiness and know which counterparties require special attention or actions.

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VI MITIGATION One of the primary intents of the CCRO’s effort is to ensure that mitigation opportunities are more widely understood and accepted. The importance of wider acceptance of mitigation techniques is driven by the power of these tools as well as by the current industry environment. Indeed, some of the underutilized tools have the ability to drive credit exposures down to a small fraction of current levels and will result in improved liquidity – especially important as the industry faces today’s liquidity crisis combined with stronger capital adequacy standards demanded by the credit rating agencies. This section defines and addresses all methods of mitigation. We compare and contrast the methods in terms of their effect on credit exposure, their costs, and their ability to be used as common business practice.

1.0 Types of Risk Mitigation There are two general categories of credit risk mitigation: (1) reduction and (2) transfer. The goal for each is to lower the overall credit exposure from an energy merchant’s trading and marketing activities. Reduction techniques are integral to a company’s credit risk management processes and include familiar techniques such as collateralization, financial/performance guarantees, exposure reducing trades, and less familiar methods such as master-netting agreements. Transfer methods move the credit exposure to another entity. These methods are less familiar and include credit derivatives, credit insurance, and an insurance financial guarantee. Multilateral clearing will have features of both reducing and transferring credit risk, depending on the type of clearing implemented. The rule of thumb in mitigating credit risk is to first reduce exposure to the maximum extent possible, then transfer any remaining credit exposure that cannot be tolerated by the firm’s overall financial risk profile. Table 2 provides a summary of methods for mitigating (or managing) credit exposure.

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Table 2. Methods for Managing Credit Risk Exposure Method

Description

Cost

Remarks

Reduction Methods Reassessment of credit limits and volumetric limits Active position management

New limits on counterparties

Collateralization

As credit limits and counterparty quality decreases, real collateral will be necessary

Exposure-reducing trades

Reduce open positions with credit Low poor; continue positions with credit rich Bilateral netting under multiple Low contracts; net financial obligations between: 1) commodities, 2) physical/ financial, 3) subsidiaries, and 4) national boundaries

Master netting

Low

Credit department actively recruits Low and tracks creditworthy counterparties

Transfer Methods Credit derivatives

Low

Transfers credit risk on a name-byVaries* name basis Credit insurance Normally covers accounts receivable Varies* risk on a portfolio; some firms have ventured into MTM risk Reduce and Transfer Multilateral Clearing Provides centralized multilateral Mod-erate netting, collateral management, and some form of performance guarantee

Reduces liquidity

Requires increased system and human resources Used and tested in futures market. Look for ways to consolidate collateral management. Need for new counterparties, but attempts to retain liquidity Some legal issues remain untested in US court

Only coverage on large names, liquidity Partial coverage, first loss provisions, time to payout 30-90 days on default Not tested in over-thecounter energy

*Cost is proportional to credit quality and size Energy merchants use many reduction methods, sometimes at the expense of product and counterparty liquidity. Reducing credit and volumetric limits reduces a firm’s credit exposure, but also lowers liquidity and ability to trade certain products. New counterparties entering the market will do so with credit risk at the top of their list when building a forward energy book. Therefore, transferring contracts from credit poor to credit rich may create a challenge. Risk transfer mechanisms will generally be high cost given the current state of the economy and investors/insurers view of the energy industry. It is not likely that credit and insurance will accept companies that are below investment grade.

2.0 Reduction Methods 2.1 Reassessment of Credit Limits One of the most risk-averse or prudent methods of mitigating credit exposure is to simply reassess the amount of credit being allocated to counterparties. Most of the industry’s credit © Copyright 2002, CCRO. All rights reserved.

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limits were determined during periods of phenomenal growth, during which access to capital was deemed to be easy and accessible. In today’s environment, it is recommended that companies reevaluate their credit limits to ensure they are consistent with today’s credit strained markets. However, this method of mitigation is hardly the “silver bullet” the industry is looking for. The largest drawback is the effect on liquidity within the industry. Simply making the playing field smaller and less populated is not the answer. Mitigation methods employing efficiencies that allow as broad a suite of participants as possible (netting and clearing, for example), while still allowing best practice safeguards are preferred.

2.2 Volumetric & Term Limits Some companies will seek to mitigate exposure to weaker credits by employing volumetric limits in addition to overall actual dollar and potential dollar (CVaR) risk limits. For example, limiting sub-investment grade counterparties to deals of no more than 50MW in size, or a predetermined tenor, regardless of the “net exposure.” This will reduce “tail risk,” or the risk that the actual dollar exposure becomes quite large due to events of extreme volatility and market movement.

2.3 Active Position Management A sophisticated credit department should be able to provide the commercial organization with real-time advice on how to best manage the selection of counterparties that will reduce or optimize overall portfolio credit exposures. For example, if the commercial organization is contemplating a long-term sale, then Credit should provide a recommended list of counterparties, some with which the company has long-term “length,” thereby reducing the overall exposure to that counterparty.

2.4 Collateralization The most widely used and accepted form of credit risk mitigation is the transference of collateral, be it cash, LOC, or financial guarantee from a related enterprise with strong credit. Collateral transference is the most easily understood method of reducing credit risk and the most direct. It is not without its drawbacks, however. The bilateral management of collateral requirements in the energy industry is very inefficient. It occurs on a daily basis and is a time consuming task. Also, absent a netting agreement or clearing platform, it is usually based on gross amounts and therefore represents an inefficient use of capital and liquidity; best practice would have the industry moving to simply collateralizing net exposures. We would recommend cash and LOCs as better forms of collateralization than surety bonds, due to the “performance risk” of surety providers paying out under claims without challenges in a timely manner. Additionally, various contract forms used in the industry allow for the margin posted, if it is cash, to be commingled with the requesting party’s funds. Therefore, we recommend the utilization of LOC capacity for those firms that would like to ensure the segregation of their collateral against rehypothecation for other collateral requirements. Generally, however, we believe that in today’s environment of tight capital and strained market liquidity, the industry must move beyond cash, parent guarantee, or LOC margining based on gross exposures towards other mitigation methods.

2.5 Exposure-Reducing Trades Exposure-reducing trades are transactions that are done in the marketplace, with a mutually agreed upon third party, for the purpose of transferring credit risk that exists between two © Copyright 2002, CCRO. All rights reserved.

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parties from deals they have already transacted and placed in their portfolios. The credit exposure-reducing transactions are done simultaneously, such that the trading position of the three parties does not change — the economic benefit of the transactions is simply the movement of credit risk to a more acceptable counterparty. Note that these are not “sleeving” trades, in which parties which cannot transact with one another due to credit constraints inject a third party between them to “sleeve” the transaction. The greatest drawback to exposurereducing transactions is if they are done when a counterparty’s credit status is rapidly declining and there is the risk of bankruptcy. In this case, creditors and bankruptcy trustees may challenge any and all of these transactions as “preferences” if done within the “preference window” as defined in bankruptcy law. (It is important to note that exposure-reducing trades are not the same as “wash” or “round-trip” trades in that they do have economic intent [reduction of credit risk] as a driver for the transaction.)

2.6 Master Netting Agreements Master netting agreements are one of the credit mitigation methods we strongly believe needs to be advanced in our industry. Bilateral standard master netting agreements are essential to a viable energy merchant industry. Netting generally occurs under two circumstances: close-out netting in the event of a termination, or netting of exposures for purposes of margining. The ability to net exposures across portfolios to mimic the true risk exposure that companies are managing is required as we go forward in today’s environment. It is important that the industry start using netting across commodities, across instruments (physical and financial), and across corporate entities. The power of such agreements has been theoretically proven by CRO analysis, and has also been practically proven via practice and implementation. More global use of bilateral master netting agreements could be accomplished via the codification of statutes and codes that would clarify the enforceability of such cross-product and cross-affiliate netting in the event of a bankruptcy event. The CCRO has also unanimously passed a resolution expressing interest in seeing laws changed to clarify the applicability of master netting agreements, not only across products and across instruments, but also across entities and geographic boundaries. The CCRO strongly supports the efforts by EEI to introduce a single-entity standard master netting agreement and credit support annex (described in Section III-1.0), and utilization of this agreement. We consider this effort, and our support thereof, to be a significant advance for the industry in terms of more efficiently using collateral, especially in today’s environment.

3.0 Transfer Methods 3.1 Credit Derivatives Credit derivatives are instruments that have their value associated with the probability of default of an underlying company. The most common example of a credit derivative is the default swap, under which payment is triggered on a counterparty’s bankruptcy or payment default. Under these events of default, the seller of the credit derivative is obligated to pay on the underlying obligation. Credit derivatives are strong mitigants to credit risk under most circumstances. If fairly priced, they are an effective means of reducing or protecting against exposure. However, the key is in the pricing and in the “perfection” of the hedge. The biggest drawback to their utilization thus far in the energy industry has been the lack of liquidity, or a secondary market, in these instruments. They are NOT widely accessible for most © Copyright 2002, CCRO. All rights reserved.

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counterparties. Therefore, as with most products where there is a thinly traded market and little liquidity, the pricing of said instruments usually factors in such limitations. Credit derivatives have been structured to mitigate credit risk, but they may not perfectly hedge the risk. That is, the payoff of a credit derivative may not match the exposure (MTM and net accounts receivable) that arises from commercial transactions. Historical usage of credit derivatives has also been tainted by contractual challenges of factors surrounding a party’s default (for example, was the default in line with defaults covered by the derivative?), and also delays in payment (payouts may take from 30 to 90 days under some circumstances). Credit derivatives are effective mitigation tools, but increased utilization coupled with increased liquidity and “fair pricing” have probably been delayed, as opposed to accelerated, by today’s environment and especially by the collapse of Enron, one of the largest participants in the credit derivative game.

3.2 Credit Insurance Much like credit derivatives, credit insurance is an effective financial product for mitigating credit risk. The major difference between credit insurance and credit derivatives is that the insurance product is usually tailored to cover a group, or portfolio of counterparties, as opposed to a single party. Policies are written by insurance companies to cover particular types of risk – retail aggregator risk, for example. They will typically cover only accounts receivable risk, although more and more are being written that will cover well-defined MTM risk. Coverage will usually be stated in terms of an overall limit for the portfolio, as well as limits for individual counterparty events. As with derivatives, until credit insurance is more widely accepted, there will continue to be issues of depth of market and fairness of pricing that need to be overcome. Credit insurance also has the additional hurdle of requiring “proof of harm or proof of loss,” which further complicates the “perfection” of the hedge (i.e., the effectiveness of insurance as a credit risk mitigation tool).

4.0 Multilateral Clearing Far and away the greatest potential for advancement for the industry in terms of credit risk mitigation, improved liquidity, and capital adequacy is through clearing. Clearing provides the benefits of multilateral netting, centralized collateral management, standard margining, and, in most cases, a credible guarantor backing events of default. Multilateral clearing may reduce collateral requirements by as much as 75—90%. It does this by simply advancing the benefits of bilateral netting to a larger grouping of counterparties. In clearing, a participant’s credit exposure to counterparties in traded contracts is replaced, in whole or in part, by credit exposure to the clearing entity. The result is that the net credit or liquidity exposure of an active participant is more closely aligned with its market risk, or the risk carried by the overall portfolio, and will benefit from the netting of all positions. The power of multilateral clearing is unmatched, and must be embraced by the industry. The following example of multilateral netting, presented in Figures 3 and 4, is based on scaled trading book data involving five counterparties. It illustrates the benefits of multilateral netting by presenting a static analysis of how exposures are netted. Figure 3 shows the exposures without netting while Figure 4 shows the exposures with netting. The arrows show the direction of credit risk imposed, with the first number in brackets representing the current MTM amounts owed and the second number showing the counterparty VaR. Only the first number comes into play in the static analysis. © Copyright 2002, CCRO. All rights reserved.

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Figure 3. Exposure without Multilateral Netting (Source: Analysis by Tractebel and Strategic Decisions Group)

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Figure 4. Exposure with Multilateral Netting (Source: Analysis by Tractebel and Strategic Decisions Group)

For this analysis, exposures are described in terms of guaranty exposure, which is the credit risk a company imposes on its counterparties. The reason for framing the analysis in this way, as will be seen shortly, is that it allows us to isolate the companies imposing residual credit risk on the industry. Following this definition, the total guaranty exposure must exactly equal the total credit risk. For example, Company C in Figure 3 imposes $37 million of total credit risk on its counterparties. Company A’s credit risk with Company C is $7 million, Company B’s credit risk with Company C is $13 million, and Company D’s credit risk with Company C is $17 million. The total for these three companies is $37 million, which exactly matches what we have called Company C’s guaranty exposure. A comparison of Figure 3 with Figure 4 shows that total credit exposure has been reduced from $172 million to about $21 million, a factor of 8. In Figure 4, Companies A and E become the only credit risks in the market since B, C, and D are all owed money by the market. Figures 5 and 6 incorporate the counterparty VaR numbers, the second number in the brackets, into a simulation to generate the full range of possibilities for the five companies given the initial situation. In Figure 5, the improvement of performance over bilateral netting is illustrated in a probabilistic framework, showing a significant reduction in guaranty exposure over a wide range of scenarios. The worst outcome for multilateral netting still vastly outperforms the best outcome for bilateral netting. Figure 6 illustrates the range of performance probabilistically, which at its worst appears to offer a 75% reduction in credit risk.

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Figure 5. Simulation of Guaranty Exposure for Bilateral and Multilateral Netting (Source: Analysis by Tractebel and Strategic Decisions Group)

Figure 6. Cumulative Probability Distribution of Exposure Reduction with Multilateral Netting

(Source: Analysis by Tractebel and Strategic Decisions Group)

The challenges facing a clearing service for OTC energy include: •

Ability to clear entire set of traded energy products − − − −

Settlement prices Liquidity spread throughout product set (increase liquidation risk in clearing) Margining (commodity, location, time periods) Options

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•

Delivery process and performance guarantees

•

Legally enforceable contracts and bankruptcy protection

•

Operational challenges of trade entry (where is the trade source), and clearing confirmation

•

Commitment of participation by merchant energy industry

•

Collateral types and centralized management of collateral

It is critical that all companies in the industry that are interested in clearing ensure that their processes, policies, and procedures are modified to incorporate this new practice. Clearing of transactions will affect all areas of the trading floor, from front office, through confirmations, to middle office recording and back office settlements. It is especially important today for companies to understand how the process of novating existing positions into a net cleared position will occur. Advisory firms are working with clearing platforms to develop tools to standardize the process of establishing clearing as a practice. Companies may either adopt one of these standardized approaches or adopt their own procedures, but they should do one or the other without delay. As part of the CCRO’s forum on multilateral clearing opportunities, we have developed a list of the criteria that potential users may use to analyze platforms and ensure they are providing a service that optimizes the benefits available. This list of attributes for analytical comparison across multilateral clearing platforms (“platforms”) follows. Attribute 1: Stimulates competition/stability/liquidity ― This attribute rates a platform on its legal enforceability. Legal enforceability can be demonstrated primarily through approval by the CFTC and secondarily through any other relevant legal approvals. These legal approvals are an important indicator that the platform will stimulate competition, stability, and liquidity, based on the premise that such approvals increase members’ confidence that the platform will effectively protect their interests. Attribute 2: Default mechanisms ― This attribute evaluates how the platform will protect members from the risk of individual defaults, as well as the potential for multiple simultaneous or associated defaults. Included within this attribute is consideration of capital adequacy or other means of ensuring capital integrity to protect against the risk of defaults. Attribute 3: Readiness ― This attribute rates a platform on two items related to readiness. First, it evaluates the ability of the platform to seamlessly connect with current business processes (i.e., compatibility with existing IT systems, current methods of operation, and current product definitions). Second, it evaluates whether the platform is ready for use or, if not, how much additional building, testing, and investment is required for the platform to become operational. Attribute 4: “All-in” costs of service ― This attribute rates a platform on capital start-up costs for members, as well as ongoing margining requirements. In addition, it rates the extent to which a platform has established clear and well-documented rules for capital and margining. Finally, this attribute examines the extent to which these rules are tailored to the needs and requirements of member companies (e.g., PGs are monetized, varying credit ratings are properly accounted for, etc.)

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Attribute 5: Scorekeeping ― This attribute evaluates the method by which a platform will mark members’ positions (e.g., the sources from which the platform will develop its forward curves). The focus is on two things: first, the extent to which the platform has developed and documented clear methods for generating a series of market curves to clear positions; second, the robustness of the methodology, such that market curves can be assumed to reflect true market pricing, thereby enabling competition through use of the platform. Attribute 6: Responsiveness to customers ― This attribute rates the degree to which the platform will be responsive to its members. Channels of responsiveness might include (but are not limited to) an industry development advisory group, member control over platform development and operation, etc. Attribute 7: Open access ― This attribute evaluates the extent to which (1) the platform is accessible to trades from multiple trade sources, (2) product definitions are open and consistent, and (3) requirements for admission and participation are objective and independent of members’ choice of trading platforms and volume of use on those platforms. Attribute 8: Proven ability ― This attribute rates the ability of a platform to manage a clearing function for energy products. The key metrics are past experience clearing energy products and/or past experience clearing other volatile products. Attribute 9: Product offerings ― This attribute rates the ability of the platform to provide tailored product offerings to its members, whether by providing a broad slate of existing products or possessing flexibility to add new product types as needed. Attribute 10: Coverage of non-standard positions ― This attribute rates the ability of the platform to handle long-term, illiquid, or other non-standard positions. There are several service providers offering a clearing solution to the energy merchant industry. None have the perfect solution, but all offer features that address the challenges at hand. The choice in front of the energy industry is whether to look to existing futures clearing infrastructure to meet its current and future clearing needs (New York Mercantile Exchange [NYMEX] and Intercontinental Exchange [ICE] through its affiliated clearing houses, Guaranty Clearing Corporation [GCC] and London Clearing House [LCH]), or look to new entrants (EnergyClear, Virtual Markets Assurance Corporation [VMAC]). NYMEX: Nymex offers a clearing process for OTC traded products that is similar to the process for existing futures contracts. Nymex has a long history, substantial membership credit quality, and access to counterparties not directly involved in the merchant energy industry. It does not have a credit rating but is supported by a guarantee fund provided by member firms and the collective credit of the clearing firms. The credit risk of a transaction is held by the clearing member firm, and all transaction processing, margining, and settlements are managed by the clearing firm. The processes for OTC clearing are new, and both Nymex and clearing firms are working out the details. Nymex now clears nine natural gas basis contracts and three power products (see Website www.nymex.com for details). Nymex is reviewing a set of new products that should be released in October 2002. All products (physical or financial) are converted to financial swaps with no particular intention to be physically delivered. At contract closure, if a © Copyright 2002, CCRO. All rights reserved.

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customer has a remaining open position it can ask for either an Exchange for Physical (EFP), where Nymex remains in the middle as guarantor, or an alternative delivery process (ADP), where the customer is matched with a counterparty and delivery credit risk is handled bilaterally. Pricing and MTM data is provided by survey methods to Nymex brokers. The costs to use the service include the clearing fee and clearing firm fees (negotiated by the clearing firm). The clearing fee for a monthly financial Henry Hub contract of 2,500 MMBtu is posted at $0.34 per side. ICE (GCC/LCH): ICE is a trading platform and offers clearing as an additional service to trade matching. ICE emphasizes that it is willing and capable of connecting to any clearing service acceptable to the energy industry. ICE’s strategy for OTC clearing has been directed at the use of existing futures clearinghouses, London Clearinghouse (LCH) and Guaranty Clearing Corporation (GCC), a subsidiary of the Board of Trade Clearing Corporation (BOTCC). The credit risk of a transaction is held by the clearing member firm, and all transaction processing, margining, and settlements are managed by the clearing firm. For ICE, LCH clears Henry Hub natural gas, and GCC will provide clearing for U.S. power products. The guarantee and clearing processes are through the clearing member firm. ICE is currently not involved in the delivery process, though it has described how delivery process will work for physical power transactions. Physical power delivery will be governed by an EEI Master Power Purchase and Sale Agreement, and 100% of the contract value will be held in escrow at GCC through the performance period. The cost of clearing through LCH or GCC will have components from the clearinghouse and the clearing firm. The clearing fee for a monthly (30-day) physical 2,500 MMBTu Henry Hub contract is $0.90 per side. EnergyClear Corp. (ECC): EnergyClear is a CFTC-designated Derivative Clearing Organization specializing in OTC energy clearing. The risk transfer mechanism is based on an extension of the member pool concept, similar to traditional clearinghouses. Therefore, the guarantee that any member receives will rely on industry-standard margin calculations designed to limit risk to a one-day price move, initial and variation margin, member contributions to a guarantee fund, a $100-million bank-syndicated lender-of-last-resort, and ultimately the members themselves. One unique feature of ECC is that it permits energy merchant companies to become direct members and thus affords them the direct credit protection of the clearing system. Also, there are multiple classes of membership, including a “recovery class,” which allows otherwise unacceptable members to participate if they maintain flat positions and other enhanced requirements to protect the clearing system. Product types are flexible and dependent on ECC member designation, margining ability, and guarantee limitations if any. Delivery process will match open positions and ask for delivery margin to cover 100% of the contract value. The exception is that gas contracts will be margined higher in the winter (200%) and power contracts will be margined higher in the summer (200%). The cost to be a member is $100,000 fixed and a $2,500,000 guarantee fund contribution. Clearing cost is $0.000215 /MMBtu, $0.01/MWh, and overhead of 2% of transaction cost over time. A monthly 2,500 MMBtu contract would cost $0.54, with no clearing member fees. (Note: EnergyClear has announced that it will make available VMAC’s system of AAA-rated financial guarantees, provided by Financial Security Assurance Inc. (FSA), covering both VaR and Mark-to-Market amounts to members, beginning in 1Q03.)

Volume 4— Credit Risk Management

VMAC: VMAC is not a clearinghouse. Instead, it is a system that (1) dynamically measures counterparty VaR (MTM) on each covered bilateral contract in accordance with industry practices; (2) provides AAA/Aaa/AAA-rated credit insurance systematically as a financial guarantee of counterparty VaR (MTM) covering both counterparties on each such contract; and (3) overlays the covered contracts with a liquidation system that replicates the results of conventional clearinghouse netting of collateral required to secure the credit insurance reimbursement obligation. VMAC has chosen not to novate trades and thus remain out of CFTC regulation as a Derivatives Clearing Organization. Its margining system is flexible and is based on VAR principles commonly used in the merchant energy industry. One of VMAC’s major shareholders is FSA, a primary Triple-A rated bond insurer for municipal and asset-backed securities. FSA provides credit enhancements to VMAC customers and insures VMAC-held collateral up to the defined margin amount. In addition to the margin amount, VMAC provides a payment to participants of VaR-based coverage so that the credit insurance for each contract covers gross counterparty VaR for both parties. VMAC will guarantee up to the margin and VaR amount but will not be responsible for liquidation risk or market risk beyond the defined margin and VaR. Therefore, the un-netted credit exposure of the participant on each contract is the AAA/Aaa/AAA-rated credit risk of FSA up to the counterparty VaR (MTM) and the original counterparty for any excess. Under the VMAC system, the original counterparty remains the same. During the delivery period, the undelivered balance of the contract enjoys the margin and counterparty VaR that applied during the pre-delivery period. Also, the account payable that results from each day’s delivery is covered by the financial guarantee. Therefore, VMAC covers both delivery risk (up to counterparty VaR and MTM) and payment risk. The collateral required to support these risks is calculated on a fully netted basis, extending the benefit of multilateral netting through the delivery and settlement periods. VMAC’s list of product types is diverse and flexible. Its only product limits will be based on data limitations on historical data and forward price curves. Fees for products will vary based on contract value and duration. For instance, a monthly physical 2,500 MMBtu Henry Hub contract would cost $1.50 per side.

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