4/20/2020 Understanding Enterprise Risk Management for Utilities © Copyright 2007, CCRO. All rights reserved. 27 with most energy utilities offering full requirements products. The risks associated with these products cannot be estimated using standard financial market tools because of the volumetric component of these markets that is highly correlated with the related markets. Second, while most utilities face some form of market and credit risk, they also face significant operational and business risks. Risks such as reliability, regulation or legislation, reputation, and environmental, may be considerably more difficult to meaningfully quantify than market and credit related risks. Most frequently, this is a consequence of the lack of a meaningful database of outcomes that can be used to populate a distribution. In addition, some risks do not have a meaningful measure. In other cases, it should be recommended that some risks, regulatory risks for example, not be measured for discovery reasons. In other cases, historical outcomes may be available but may be too infrequent to generate predictions with any degree of confidence. As an example, a utility may have detailed historic data on reliability, but this will not necessarily predict the range of potential outages in the next peak period. As a result of the unique risk profile of utilities, these companies should develop customized metrics and tools to measure the risks of their portfolios. This, however, is beyond the scope of this paper. While the Earnings-at-Risk measure described before will be applicable to utilities, stress-testing and scenario analysis should be employed liberally to develop a framework for understanding the unique nature of the risks a utility faces. Stress Testing refers to creating defined scenarios in which one or more risk variables are changed in order to understand their impact on measured outcomes and understand overall firm risk sensitivities. These are frequently utilized in order to, for example, measure the impact of a large movement in commodity prices. In a utility environment, a stress test might be employed to test the impact of an increase in fuel prices or the effect of a large rate increase on demand consumption. In most cases, a number of tests are performed on a regular basis. These could include scenarios such as a large movement in the forward price curve, adverse environmental legislation, assumed regulatory decisions, or the adverse effects of workforce issues. The results of the tests are reported and used by risk management to test the sufficiency of current hedge programs, the impact on the rate base, or to test new remediation strategies. Additional depth is obtained when the tests are performed with multiple variables. It is important to note that the stress tests themselves may not necessarily be probable or even possible outcomes. The value provided is in giving management a fuller understanding of sensitivities and relationships among different risks. To ensure that stress tests provide their maximum benefit, a standard set of tests could be performed on a regular basis. Reporting of the results should explain the implications of changes in the results from one run to the next. At the same time, management should not be limited by the defined test set. In addition to the normal stress tests, new tests should be periodically run to ensure that new risk relationships, or unexplored correlations in the existing set of risks, are analyzed. Scenario Planning refers to creating scenarios to better explore the risk environment and the sufficiency of risk management plans. The critical difference from stress testing is that scenarios need not be quantitative in nature. While the quantitative risks evaluated in stress tests may often