Tackling complexity in the energy market

The risks

Oil and gas extraction, often in extremely hostile environments, is risky business. There will always be inherent dangers is processing and handling volatile substances, and accidents are inevitable, but it is their magnitude that can be worrying. In 2010 the explosion at the Deepwater Horizon rig could be seen 35 miles away with the aftermath resulting in an estimated 20 million gallons of oil released into the sea, severe damage to the environment, the loss of 11 lives, disrupted supply chains, and a final insurance bill that will amount to many hundreds of millions of dollars. Added to this we have the natural perils that many rigs and platforms are exposed to, such as hurricanes and earthquakes, and it is no surprise that a complex re/insurance market has evolved to assume and finance these risks.

Coverage

To meet the needs of the energy industry the re/insurance market has developed a sophisticated product offering which includes property damage, removal of wreck, control of well, loss of income, and third party liability. Due to the size of policy limit required, and the niche nature of the subject, the market provides coverage through subscription policies and/or through a layered programme structure. The market also provides cover for all the different perils that the platforms are exposed to, either as an ‘all risks’ policy, or through issuing separate policies for each named peril. With the cover types often interacting with each other, and with sub-limits applied at various levels, even the calculation of exposure at the insurance level is complex for a simple loss scenario, and obviously compounded at the reinsurance and retrocession level with potential accumulations across cedants.

We find that as a result of the dynamics of the original risk, and the cover provided by the re/insurance market, energy is a class that is exposed to nearly all the types of claims aggregation that are seen in the re/insurance market. For a loss involving a single platform there can be an accumulation of limits provided for different cover types, and an accumulation of policies, as many insureds may have an interest in the asset as an owner, manager, operator, or sub contractor.

There is also the possibility of having multiple platforms involved in a single event, either as the result of a loss of a complex (a linked structure of multiple platforms) or through a natural catastrophe event. It is clear that risk management is a vital element to the successful operation of the energy market, and that a full understanding of exposures should always be a requirement prior to committing capital to this class. With the magnitude of potential losses, the failure to calculate exposures correctly could not only damage a company’s earnings, but could erode capital and threaten its ability to continue underwriting this class.

Risk management analysis

"Over time we continue this distillation process of learning more about the event and being able to remove or add scenarios, reaching an increasingly accurate and reliable exposure figure."

When it comes to risk management one of the lessons learned from the Deepwater Horizon loss was that a realistic disaster scenario for a platform can be the total loss of a number of policies for a number of different assureds and that in calculating exposures a probable maximum loss (PML) of 100 percent would not be overly pessimistic. When modelling total losses the calculation of the loss severity, and reinsurers’ exposure, is straightforward as it is based on the policy limits, but it is often difficult to identify the various parties that may have an interest or liability in such a scenario. There is often limited data and information available prior to an event regarding the parties associated with a rig or platform, and as loss surveying and legal arguments become more complex, the number of potential insureds involved in a litigation is always growing. From a risk management perspective it is important that a reinsurer is able to identify the possible parties involved in the loss and to generate and process various scenarios to give itself an understanding of the possible exposures it may face.

For an accurate and comprehensive risk management process underwriters must also consider partial losses, and here the situation is much more complicated as many more scenarios are possible— each giving rise to different levels of losses, to different policies or policy sections. To have a full understanding of the underwriting risk being assumed, underwriters need to have analysed as many of these outcomes as possible and to ensure that they are prepared, from both a capital and a risk appetite point of view, for those eventualities.

What this means in practice is that there is a need to have a risk management system in place that can generate these scenarios andthen process them to calculate the resulting portfolio loss. As we have seen, many possible scenarios need to be considered and the system needs to be dynamic and capable of running simulations so that the (almost impossible) process of having all the events user- defined is avoided.

Loss evolution

One of the final features required for good risk management is the ability to understand actual events as they unfold, as even after the initial event there are still many possible outcomes, and what the re/insured consequences could be. This requirement was highlighted during the event involving the Elgin platform that suffered a gas leak in March 2012 as there was a great deal of uncertainty as to the final outcome even after the initial leak happened. This is a common feature of natural perils modelling where, for example, possible storm tracks are analysed once a hurricane starts to form, but it is not usually done for specialty classes like energy. Such analysis may be done in a spreadsheet following the start of the event, but this can take time and is often a clumsy way to arrive at exposures.

What is needed is a system in place that can call on before-the- event scenarios, but make it conditional on the event that has begun. In this instance we could investigate all the scenarios we had previously generated for the Elgin platform, review them in light of what has actually happened (some may be capable of being discarded, or others added that were not previously considered possible), and by considering the relative probabilities arrive at an expected loss or distribution of possible portfolio losses for the event. Over time we continue this distillation process of learning more about the event and being able to remove or add scenarios, reaching an increasingly accurate and reliable exposure figure. Ultimately underwriters have a constantly evolving, real-time, picture of their exposure that is based on the most up-to-date information available about the event.

Conclusion

The offshore energy market is a class that has a volatile and potentially catastrophic risk profile, with many different accumulations assumedby re/insurers with a requirement to manage them. At the heart of a good risk management process is the ability to generate and understand the financial impact of various scenarios, whether they be a single risk loss, an accumulation of different cover types and policies, or a catastrophe involving many assets. The key to doing this is having a sufficiently sophisticated system that can cope with the complexities of the energy market: interrelated cover types, sub limits at various cover levels, multiple assureds at a single platform, all risks and named perils cover, and an underlying risk model that understands insurance, reinsurance, and retrocession.

Matthew Maddocks is product manager for Russell Group. He can be contacted at: mmaddocks@russell.co.uk