Section I Identifying and understanding GAIL’s risk exposure

1. Section IIdentifying and understanding GAIL’s risk exposure

2. Overview • Analyzing GAIL’s risk exposure • Tools for quantifying risk • Impacts of risk on corporate performance – and how risk management can improve results

3. 1. Analyzing GAIL’s risk exposure To put it simply and directly, if the bosses do not or cannot understand both the risks and rewards in their products, their firm should not be in the business. William J. McDonough, PresidentFederal Reserve Bank of New York"A Regulatory Perspective on Derivatives"

4. Operational environment supply decisions prices Outputs Inputs upstream investments marketing Decisions

5. AN EXPLANATION OF RISK, FROM CONTINGENGY ANALYSIS (www.riskglossary.com) • Risk has two components: uncertainty, and exposure. If both are not present, there is no risk. • If a man jumps out of an airplane with a parachute on his back, he may be uncertain as to whether or not the chute will open. He is taking risk because he is exposed to that uncertainty. If the chute fails to open, he will suffer personally. • In this example, a typical spectator on the ground would not be taking risk. They may be equally uncertain as to whether the chute will open, but they have no personal exposure to that uncertainty. Exceptions might include: • A spectator who is owed money by the man jumping from the plane • A spectator who is a member of the man's family • Such spectators do face risk because they may suffer financially and/or emotionally should the man's chute fail to open. They are exposed and uncertain.

6. AN EXPLANATION OF RISK, FROM CONTINGENGY ANALYSIS (www.riskglossary.com) A synonym for uncertainty is ignorance. We face risk because we are ignorant about the future. After all, if we were omniscient, there would be no risk. Because ignorance is a personal experience, risk is necessarily subjective. Consider another example: A person is heading to the airport to catch a flight. The weather is threatening, and it is possible the flight has been cancelled. The individual is uncertain as to the status of the flight and faces exposure to that uncertainty. His travel plans will be disrupted if the flight is cancelled. Accordingly, he faces risk. Suppose another person is also heading to the airport to catch the same flight. This person has called ahead and confirmed that the flight is not cancelled. Accordingly, she has less uncertainty and faces lower risk. In this example, there are two individuals exposed to the same event. Because they have different levels of uncertainty, they face different levels of risk. Risk is subjective.

7. Virtually every entity in today's world is exposed to economic risks. Some of these risks are unavoidable, some can be avoided with good management. Likewise, some risks are, in one way or another, insurable, others are not. The character of risks is not always evident. E.g., the costs of drilling rigs and oil field services are not “external”, but are correlated with hydrocarbons prices – so they can be managed through long-term fixed-price or price-indexed contracts with service providers, or through hedging. Risks can be managed with foresight. Damage can be controlled with hindsight. Your choice. Coopers and Lybrand, L.P.Advertisement in The Wall Street Journal, December 7, 1995

8. The Universe of Risk Financial Risks Strategic Risks • Well developed risk management practices and supporting industry • Risk financing through derivatives • Demand projections often have little credibility • Operating costs often are underestimated • Unforeseen capital costs can cause major problems • No risk finance or other risk transfer methods • Creditdefault • Marketdemand • Financial market risks • Operating costs • Interest rate changes • Unexpected capital costs • Currency/foreign exchange fluctuations • Customer/industrychanges • Liquidity,cash flow issues Integrated Risk • Well-developed risk management practices and supporting industry • Risk finance traditionally through insurance, but recently through captives and capital markets products as well • Information systems • Property damage • General liability/legal risks • Accounting/control systems • Developing risk management field • Some risk financing in business interruption insurance; risk transfer through PEOs; business interruption services • Workers compensation • Key managers • Natural disasters • Supply chain • Business interruption Operational Risks Hazard Risks Source: Mercer Management Consulting

9. Market risks: normally hedgeable Source: Goldman Sachs

10. Operational risks: usually not hedgeable, but manageable. Source: Goldman Sachs

11. Risk impact has different components: • Margin risk: the company’s profit margin is at risk because of a mismatch between the cost and revenue sides • Budget risk: the risk of exceeding previously set budget targets • Cash flow risk, creating liquidity squeezes and hindering investments • Performance risk: the economic environment can become prohibitively difficult.

12. The major sources of risk • Business risk (production, human, political….) • Market risk (direct or indirect) • Credit risk (default by a counterparty) • Operational risk (human errors, system failure, inadequate procedures and controls) • Liquidity risk • Legal risk • Model risk: inadequate model, or inadequate use of a model.

13. For example: the LNG Value Chain Shipping Upstream Projects Buying & Receiving Distribution End-Users Power Field Generation Development LNG Gas Gas LNG Gas Gas Distribution Receiving Terminal Shipping TownGas Liquefaction ~ $0.5bn ~ $2 bn ~ $0.5-1.0bn ~$0.1s bn ~ $3 bn All links of the chain are capital intensive businesses Source: ExxonMobil

14. For risk analysis: • identify the critical processes and components (go for the « doctrine of no surprises ») • understand their risk implications • identify the resultant cash flow risks (« cash flow at risk ») • identify the wider corporate risks.

15. Risk: Inability to meet demand Fluctuating demand for transport: with strong demand, both gas prices and transportation costs pipeline charges are high. Risk mitigant: Store large quantities of gas near market Derivatives, cash reserves

16. Analyzing price risks: starts with « what is the impact of a 1$ price change on company profits? And then, look at correlation… Urea Coal Henry Hub Commodities Crude oil Total LIBOR Interest rates Yen Exchange rates US$ Individual risks Aggregaterisks Total risks

17. One should also consider risk by business unit; e.g., at 1% probability: loss 1 2 3 4 5 6 7 8 Business units

18. And you can compare this with the units’ shares in expected profit and allocated capital…. profit loss capital 1 2 3 4 5 6 7 8

19. The company’s major unit is underperforming…. profit loss capital Doing very well 1 2 3 4 5 6 7 8

20. Return on capital employed Average return Standard Risk adjusted Worst case on capital deviation return on cap. at 95% Current businesses 1. 2. Potential new businesses 3. 11.4 % 9.8% 1.1% -2.2% 4. 9.3 % 6.3% 1.4% 0.2% What new business will you invest in? Source: Goldman Sachs

21. 2.Key tools to quantify risks You take risks in whatever you do. But if you understand, measure and account for them, that should keep you out of trouble. Dennis Weatherstone, Chairman and CEO, JP MorganBusiness Week, October 31, 1994

22. Risk management is not to ensure that losses do not happen, but to ensure that losses are kept within « acceptable limits » As such, it is a top management and Board responsibility.

23. Using models to assess risks The use of a formal model can help company treasurers, and other managers, to get a clearer idea of the extent to which the company is exposed to price risk. These models can be used for the company as a whole, and also, for particular instruments (e.g., one complex derivatives contracts), or group of instruments (e.g., the total exposure of one division). There are four major types of models, which are often used to complement each other: • asset/liability analysis • value-at-risk (VAR) • stress-testing • Risk-Adjusted-Return-on-Capital (RAROC)

24. Too large a proportion of recent "mathematical" economics are more concoctions, as imprecise as the initial assumptions they rest on, which allow the author to lose sight of the complexities and interdependencies of the real world in a maze of pretentious and unhelpful symbols. John Maynard KeynesThe General Theory of Employment, Interest and Money, 1936 Mathematical risk quantification has become a pseudo religion that pacifies our insecurity. Models have become sacred pagan gods, but God's wrath can change. Randall PayneRisk Professional, September, 1999

25. How does one determine « acceptable limits »? • What maximum loss is the company willing or able to withstand in a given period, at a given confidence level. • Two issues: • Expected loss: the company has to build this into the pricing of its products. • Unexpected losses: the company has to ensure that it has the « economic capital » to deal with these.

26. Quantifying « unexpected losses »: The sum for each of the company’s operations, corrected for correlations/portfolio effects, of the following: Probability of default X Exposure at default X Loss given default So, good data are essential. « Garbage In, Garbage Out »

27. Measuring economic capital is an art rather than a science. • Still, there are tools for quantification. And even an idea of the economic capital that needs to be put aside to ensure survival of certain activities within a certain confidence interval allows senior management/the Board to: • allocate capital along business lines • screen proposed new transactions/counterparties/ business lines (is the Risk Adjusted Return on Capital high enough?)

28. Asset/liability analysis The traditional approach to analyzing a company’s risk exposure is Asset/Liability Analysis. This approach works as follows: 1. A hypothetical scenario is selected that describes how various financial variables - commodity prices, interest rates, inflation, etc. - might evolve over an extendedhorizon. 2. This scenario is used to simulate the cash flows and the accounting value of assets and liabilities as they would develop over time, assuming that the scenario becomesreality. 3. The process is repeated for other scenarios in order to consider a range of future outcomes.

29. The actual variables incorporated into scenarios will depend on the assets and liabilities considered. For example, an oil refinery might use asset/liability analysis to analyze the likely profitability of an expansion programme. A scenario might project paths over the next ten years for swap interest rates, currency exchange rates, and refinery margins. Likely, the scenario would reflect reasonable relationships between these variables. A sophisticated analysis might make other assumptions as to how the refiner would alter its risk management behavior in response to changing market conditions.

30. Asset/liability analysis is a flexible methodology that allows the user to test interrelationships between a wide variety of risk factors including: market risks, liquidity risks, actuarial risks, management decisions, uncertain product cycles, etc. It has the shortcoming of being highly subjective. It is up to the users to decidewhat are appropriate scenarios. The user must also analyze the results and determine their significance. Accordingly, asset/liability analysis is not so much a measure of risk as it is a tool which supports the analysis of risks.

31. Asset/liability analysis is slowing being supplanted by more objective statistical measures of risk. This is happening for two reasons: • As markets become more liquid, market valuations are becoming available for a greater range of assets and liabilities. This facilitates statistical risk measurement. • Advanced technology is making possible many forms of advanced statistical risk measurement that were not possible in the past. There will, however, always be illiquid assets or liabilities for which market values are unavailable, so there should be a continuing role for some forms of asset/liability analysis.

32. Value-at-Risk (VAR) The Value-at-Risk (VAR) approach provides a measure that indicates how much money a company could lose by holding a position for a specific period of time, given a certain confidence interval (logic: the company has to hold enough capital to cover, say, 84%, or 99% of possible losses). In other words, this approach: 1. Calculates the dispersion of prices, interest rates, and other assets which are important for the company around their trend. 2. Then calculates for example the standard deviation of prices etc. 68% of the time, the asset prices fall within the average plus or minus one standard deviation - e.g., the average oil price is 30 US$/barrel, and the standard deviation is 5 US$, then 68% of the time, the oil price will be between 25 US$ and 35 US$ a barrel. 3. A monetary value is then given to the negative results: e.g., how large will the company’s loss be if the price is 25 US$ a barrel? This monetary value is a “Value-at-Risk” at this 16% risk level. Normally, these values are also calculated for other risk exposures (e.g., 10%, 5%, 1%).

33. What is the likelihood of prices falling below certain levels? And what is the corresponding loss?

34. In other words, VAR forces a company, or the manager of a portfolio, to make a public statements along the following lines: “With the strategy followed so far, we have made nice profits.  However, if we continue in this manner, there is a chance of one out of 20 that in the coming year, we will lose at least…10million...100 million …1 billion US$….” And implicit in this is that “it can be even worse”.

35. For a portfolio of assets (e.g., exposure to oil price risk, interest rate risk, etc.), the covariance of asset prices is calculated, to arrive for the total risk for the full portfolio. Naturally, this quickly becomes complex, and in practice, one needs specialized software for a VAR analysis. The three most common softwares are: • The most popular is RiskMetrics. RiskMetrics publications, as well as sets of data that can be downloaded in order to keep the model up-to-date, are available at URL http:/www.riskmetrics.com • There are also a number of other commercial softwares. • Companies often develop their own in-house programmes. These softwares vary in sophistication. Some use standard deviations (which presume a normal distribution of values), others use Monte Carlo simulation to cope with the risks of the skewed distribution of returns of certain assets (e.g., most commodity prices are skewed to the right).

36. Risk Metrics Risk Metrics is a tool for measuring risk, based on a huge data set of volatilities and correlations between various kinds of financial instruments. These instruments are: Basic assumptions for the model are: • Normality of returns • Forecasts of volatilities and correlations using Exponentially Weighted Moving Average Model (EWMA) which gives the latest data more weight and therefore more influence in the estimation. fixed income (government & non- government) Commodities Equity Foreign exchange

37. Risk Metrics is a valuable tool in the sense that it provides a standardized measure of risk. But it can become risky if the users are not aware of its assumptions as well as the the limitations of the VaR concept in itself. VaR models such as Risk Metrics can become misleading if : • Estimation of probability distributions of prices is not adequate: crashes occur in real markets much more often than a normal distribution would predict. • Valuation models for the securities in the portfolio, such as Black and Scholes are based on mistaken values. For instance, prices are usually difficult to calculate in illiquid markets or for non-continuously traded assets. Then VaR will then be calculated for a portfolio whose value is wrong in the first place.

38. Value-at-Risk – the problems The Value-at-Risk approach has a number of important weaknesses: • It can be tempting for some to use it as a “black box”, accepting the outcomes without any real understanding of the ways that these outcomes were arrived at. This creates complacency, and may lead to wrong decisions when market conditions change. The large hit you will take next will not resemble the one you took last

39. - related to this, VAR is based on certain assumptions, which may change over time. In many companies, risk managers are given a “Value-at-Risk”, a risk limits to which they can be exposed to before senior management intervenes. Such use is sound, aslong as traditional prudential controls are not weakened. Traders with frequent losses hurt you but they are not likely to blow you up. Beware of traders who make a steady income

40. VAR is better as a tool to analyze the relative benefits of different business activities within a company than to analyze the risks of the company as a whole. Thus, it is a relatively good tool to decide how to allocate capital, reorient business activities and so on; but, although it is frequently used for this, it does not give an “overall risk measure” for the company. - As it was developed by and for bank operations in financial markets, VAR was developed as a tool to get an estimate of the potential losses between now and the next day, or two weeks. It is not necessarily a good tool for estimating longer-term risk exposure. - VAR is based on the law of averages. Never cross a river because it is “on average” one meter deep A statistician can have his head in an oven and his feet in ice, and he will say that on the average he feels fine.

41. The Value-at-Risk method is based on assumed volatilities and correlations for various market variables, typically based on historical data. In other words, a VAR-model assumes that market behavior is stable, and that the statistical characteristics which the markets have displayed in the past will continue to drive their behaviour in the future. If the system is used to force a bank’s or company’s traders (speculators) to go for assets with a historically low VAR, it can force them to ignore the real risk of a change in these historic relationships (e.g., invest in a traditionally stable currency, even if there is a high risk of devaluation). Therefore, VAR does not encompass the risk that market behaviour may fundamentally change. In order to provide some protection against this “model risk”, stress testing is normally used to determine what would happen if some of the critical assumptions of the VAR-model no longer hold true. In effect , VAR should always be combined with stress-testing.

42. Stress -testing Stress-testing isa risk analysis method whereby the performance of an instrument, or a portfolio of instruments (including the whole of the company) under one or a handful of user-defined market scenarios is tested. Stress testing is frequently used to supplement Value-at-Risk measures. The major weakness of stress-testing is that the limited number of scenarios chosen always will miss the vast majority of possible "stress" events. The results should thus be used carefully.

43. Stress –testing- an example Assume that jet fuel prices and gasoil prices are historically closely correlated. A VAR model that incorporated this historical correlation into its analysis would ignore the possibility of the two commodities dramatically moving against each other—more specifically, it would recognize the possibility, but assign it a very low probability. With a stress test, the risk manager could directly analyze what might happen if the correlation between the two commodities broke down. This could be done by considering two scenarios: • Gasoil increases in value relative to jet fuel by 10% over the next week. • Gasoil decreases in value relative to jet fuel by 10% over the next week.

44. The two scenarios have nothing to do with the historical trading patterns of the two commodities. No probability is assigned to either scenario. The risk manager simply asks: "what would happen if one of these scenarios came to pass?” By analyzing the impact that stress scenarios would have on a portfolio, the user can identify exposures that might not be identified by statistical risk measures. These could include risks associated with cross hedges or way-out-of-the-money options. As with asset/liability analysis, results are highly sensitive to user assumptions.

45. Similar stress tests can be done for other « random hazards ». And the Board/management can decide on how much risk they are willing to take with respect to such hazards. E.g., unexpected random hazard loss should not exceed 10% of profit, or reduce equity by more than 2%, or cash flow by more than 5%. (Source: AON)

46. Risk-Adjusted Return On Capital (RAROC) RAROC is a comprehensive risk management tool; in a way, VAR is one of its constituent elements. Just like the VAR approach was made popular when, JP Morgan made its RiskMetrics programme available on the Internet in 1994, so the RAROC approach became accessible with Bankers Trust’s publication of the methodology in 1997. The VAR approach only looks at risk. It does not balance risk and return. The RAROC approach is meant to correct this weakness. RAROC allows to link returns and risk

47. The RAROC approach Step 1 Create a formal model of the risk portfolio. For example, what is the exposure to US$ risk; what is the exposure to oil price risk? Company risks are thus put into pre-set categories, with the correlation between categories already built in. Estimate “capital at risk”. This is calculated as the amount of capital needed to cover the worst 1% of possible outcomes, given historical risk distribution - in the Bankers Trust model, a Monte Carlo simulation is used to identify the losses resulting from the 1% of worst outcomes. Attribute the capital at risk over different business units, categories of instruments, etc. The model then allows to test different scenarios: adding new positions, adopting a hedging strategy, changing asset allocation. Sensitivity analysis is also possible, to identify the possible effect of hypothetical changes in interest rates, exchange rates, etc. Step 2 Step 3

48. From an operational point of view, RAROC allows a company to segment risk into all of its components. And not in an abstract way, but actually, by attributing the amount of capital which is at risk in each component. This capital at risk can then be compared to the returns made by this component. In other words, companies can use RAROC to ensure that the magnitude of returns fits the magnitude of the risks it is taking. If the two are not commensurate, the company can decide to allocate its capital in a more attractive manner. RAROC is a tool to help a company determine whether it has the right return the right mix of assets the best possible management of assets

49. RAROC allows for a more efficient capital allocation, and thus, expected return can be improved while keeping risk constant. At the operational level, RAROC allows a company to evaluate whether the risk-adjusted return on a possible new transaction is good, compared to the transactions already in the portfolio, or compared to a certain objective. On the other hand, as the scope of RAROC is rather broad, it requires a more extensive approach to risk management than do other approaches. Most importantly, a set of clear policies from senior management (including procedures and standards) is required together with a level of organizational maturity that ensures the needs of the business are not stifled by the requirements of risk tracking.

50. USING THE VARIOUS MODELS : THE PRACTICAL ASPECTS For commodity firms, there are really two factors that enter into the decision whether or not to use these models, and if any, which ones should be used. These factors are: • the complexity of the model • the direct and indirect costs of using the model Complexity The various models are only tools, so management should understand them, and their use.In all cases, the strength of the model will depend on the quality of the underlying data. Using sophisticated models in environments were these data are weak, or not very significant (e.g. due to government interventions) is risky. Cost The first cost that companies should consider is the actual cost of buying the computer software. This can vary from 5,000 US$ for a simple VAR system, to one million US$ for the complete RAROC package. Then, they should look at the costs of adapting this system to the company’s needs. Larger companies can also outsource the activity to an independent firm.