a different view of your insurance programme
Introduction – the traditional single view of risk
These days data on many aspects of the performance of power and renewable energy companies is widely available, but many companies miss the insight contained within the data and as a result make sub-optimal decisions. So how are leading power and renewable energy companies combining data with focussed analytics and deep industry knowledge to view risk in a different way in order to make better quality risk financing decisions?
Too simplistic? Traditionally, power and renewable energy companies have insured their risk exposures on an individual basis with reliance placed on historical losses to assess risk, usually by considering each class of insurance in isolation. Premium, market capacity, deductible and insurable limit were the main drivers, with only limited analytical decision support undertaken to assess placement outcome and pricing. This single view of risk does not take into account the true nature of risk, which is more complex and includes dependencies within and between risk exposures that can now be better understood by combining data with modern analytical capabilities.
Too complex?
In addition to buying insurance as individual lines of cover, the various insurance lines are often bought with different renewal dates, with many local policies stretching across different geographies as well as varying levels of deductibles and limits. This complex structure of cover makes it difficult for key decision makers such as Treasurers and CFOs to understand precisely how their company is protected in the event of a series of losses, and as a result may lead them to underestimate the true value of insurance as a hedge.
Differences from other hedging strategies This is in stark contrast to the value that power and renewable energy companies perceive from transferring risk by purchasing hedges in commodity markets, interest rate and currency markets. Due to the binary nature of such structures (there is only a pay-out if an index or a currency falls below a pre-agreed value) they are often viewed by Finance functions as simpler to understand than insurance.
Moreover, layers of hedges across different risk types may be bought to protect the organisation from scenarios that are deemed too risky without transfer of risk to the external market. It is this simplicity that is regarded as particularly attractive by CFOs and Treasurers, compared to the perception that insurance is more complex to understand and hence use as a hedge for effective risk transfer.
Common insurance structure How then should these different points of view be reconciled? A good place to start is a common representation of the insurance structure that is purchased by the organisation. The structure is often depicted as a series of bars or towers, where the height of each bar approximates to the amount of cover bought, and may look like this: Does this structure work when the company is under stress? Whilst this depiction is helpful for understanding exactly what amount of cover has been purchased for each line of insurance, it is less helpful when seeking to understand the protection afforded to the organisation in times of financial stress. For this to become easier to understand, we need a different viewpoint.
Retained risk and expected cost One viewpoint that CFOs and Finance teams will be familiar with is one that identifies the trade-off between risk and return. For our purposes we will amend this slightly to show the trade-off between retained risk and expected cost. This view has been designed so that it is easy to see the merits of different financing strategies as well as their impact of the organisation’s bottom line.
In Figure 3:
The objective is to reduce the amount of retained risk and at the same time reduce the expected annual cost and move to a more efficient programme, closer to the edge of the cloud in the above diagram.
Towards the efficient frontier – and a better understanding of risk By combining data, industry knowledge and modern analytics, a better understanding of the company’s risk exposures and their variability may be obtained. This insight will often reveal a very different picture from the traditional siloed view of considering different classes of risk in isolation. A significant benefit of this approach is to show where concentrations of risk occur as well as where there are currently inefficiencies in the transfer of risk off the balance sheet.
Combining analytics with industry data to identify trade-offs
As a result, many leading companies are now beginning to embrace combining analytics with industry data to better understand risk at a portfolio level, and hence to understand the trade-off between the cost of retaining vs the cost of transferring risk.
This deeper understanding of the correlations of risk helps to identify ways to reduce volatility by measuring the effects of diversification, and may be used to develop alternative strategies. These strategies may then be assessed and compared using the lens of riskiness versus expected cost shown above.
This path to efficiency was highlighted to a recent client in the following diagram and shows three different options, all of which are more efficient than the current strategy. They represent an annual cost saving to the company, as well as significantly de-risking the balance sheet at the same time.
Advantages of optimization The proposition for companies here is clear:
Methodology In practice, this is carried out in 6 distinct steps:
Developing tailored cover The increased availability of data and use of analytical methods is also leading to the development of alternative forms of risk transfer, such as parametric solutions, which can transfer financial volatility arising from weather related events or natural catastrophes away from company balance sheets. By understanding the variability inherent in risk exposures that are not necessarily insurable, it is possible to use analytics to develop tailored cover based on measurable factors such as volume of rainfall, wind speed, footfall and temperature.
Decision making audit trail Another important benefit of using an analytical approach is the creation of an audit trail of decision making for risk financing. By considering current risk exposures, the efficiency of both the existing risk transfer programme and of alternative structures, it can be shown that an objective and robust approach has been followed that takes into account the interdependencies of risk, and consideration of the merits of different strategies before a decision is taken.
Benefits of this approach
More generally, companies that use this approach find that they:
Conclusion – time for a new conversation? To conclude, a couple of recent examples will help to show the breadth of questions that can be answered by this approach.
Large European public utility The Strategic Risk Consulting team within Willis Towers Watson carried out a detailed analysis of both the global natural peril and man-made risks the utility is exposed to. The results and expert interpretation of this analysis provided the client with a significantly improved understanding of the size of potential losses from the portfolio for both property damage and business interruption, which was vital in helping to reset the insurance limits and deductibles as well as determine a fair allocation of premiums between the businesses units across the world.
Global Energy Company This client carried out a comprehensive risk optimisation exercise to better understand their total risk exposures and to identify the key drivers of risk, by geography and class of risk. The risk profile of the company was quantified, which demonstrated significant inherent risk in a single business unit. As a result, the company decided to sell off the highest risk business unit, and optimized insurance program for remaining business units.
Andy Smyth is Senior Partner in Willis Towers Watson’s Structured Risk Solutions division in London.
