Actuarial Risks -- Operations & Markets Research Paper Starter

Actuarial Risks -- Operations & Markets

(Research Starters)

Pure risk is defined as a situation that involves a chance of loss without chance of gain. A good example of a pure risk is the chance that a fire will happen or it will not. Traditionally, pure risks have been considered insurable. In today's complex world, there are many risks that may fall into the category of pure risk- but are not insurable. Examples of these risks are acts of terrorism, pandemics or major catastrophic events. Insurers are struggling to deal with uncertainty in insurance markets in an increasingly risky world. Insurers rely on historical data to model risks and determine what premiums are needed to cover the risk of loss. Insurers are not able to model risks for many of today's pure risk scenarios because there is not sufficient data on which to base risk models or premiums. In some cases, insurers are not able to insure against pure risks because the premium costs are not reasonable. In some cases, corporations are choosing to self-insure against large risk scenarios. Today's insurance marketplace is faced with challenges in creating and maintaining sufficient capital through selling premiums. Insurance companies and reinsurance companies are integrating their risk strategies with financial markets to greatly increase equity capital and disperse risks across broad financial markets. Some of the instruments being used today are CAT bonds and sidecars which allow investors in equity markets to diversify their investment portfolios while infusing needed equity capital into insurance markets.

Keywords Cat Bond or Catastrophic Bond; Illiquidity; Indemnity; Industry Loss Warranties (ILWs); Insurance Linked Securities; Insurance Securitization; Law Of Large Numbers; Portfolio Insurance; Pure Risk; Pure-Risk Hedging; Reinsurance; Retrocession; Sidecar; Speculative Risk

Actuarial Science: Actuarial Risks: Operations


The best case scenario of a pure risk situation is that no threats to an asset occur. In other words, if a company insures its building against the danger of fire and no fire occurs, that is the best case scenario of insuring against the pure risk of fire. The insurance against a pure risk offers no option for a company to profit. "Pure risk is basically the risk to an organization resulting from physical, environmental or human threats to a business or part of that business. It might include such things as fire, flood, earthquake, accidents, injuries, industrial action, kidnapping, hostage taking, sabotage, plant failure, theft and fraud, just to name a few. As you might imagine, all of these scenarios are likely to result in major losses and require preventative action where necessary (or possible)" (Pure Risk Rating, 2004, Glossary).

The Use of Insurance

“Insurance works best for high-frequency, low-severity events, which are statistically independent and have probability distributions that are reasonably stationary over time” (Cummins, 2006, p.337). Insurers are in the business of assuming risk for individuals and businesses. In order for insurers to remain financially solvent and insure sufficient capital to pay claims, the insurers must apply what is known as the law of large numbers. In essence, insurers diversify their risk by pooling large numbers of policies together and relying on statistical models to insure that payouts are less than premiums collected from policy holders. Statistical modeling also allows insurers to predict losses using historical data that samples loss distributions. Insurers rely on multi-year data to project losses and estimate premiums based on the models. Historical data allows insurers to predict future losses and raise needed capital through premiums based on those projections. When heavy losses occur in a short period of time, insurers have difficulty estimating premiums and capital needs. Insurance companies do much better at insuring high frequency and lower impact events that can be modeled and quantified.

Statistical models currently predict that a major catastrophe is likely to happen in coming decades. A high severity event resulting in greater than $100 billion of losses in a high population state such as California or Florida could swamp the traditional insurance and reinsurance market. While such an event has the potential to adversely impact an insurer's capital reserves, financial markets could easily absorb such losses and have little noticeable impact on investors. "Securitization extends the scope of diversification from insurance and reinsurance markets to the entire securities market" (Cummins, 2006). The diversification of insurance to financial markets is seen most obviously in the rise in popularity of CAT bonds and Sidecars which will be discussed later in this essay.

The current market in the insurance industry can be termed as a hard market. "Hard markets are triggered by capital depletions" (Cummins, 2006). From a historical perspective, the early 1980s saw a depletion of capital which resulted from a high number of commercial liability claims, coupled with a drop in interest rates. A similar market impact was experienced from 1990- 2001 and was the result of Hurricane Andrew, the California earthquake in Northbridge and the 2001 terrorist attacks in New York and Washington. While the events in these two scenarios are different, the resulting impact on insurance markets was remarkably similar (Cummins, 2006).

Prior to 1986, the number of catastrophic events occurring in a year was fewer than 150. Since 1993, the number has increase to more than 270 a year. The most costly of these disasters have disproportionately occurred in recent decades. Hurricane Katrina, the mostly costly natural disaster ever, had projected losses of $40-60 billion- compared with the World Trade Center attacks at $40 billion and Hurricane Andrew at $22 billion (Cummins, 2006).


The New Sources of Risk

Today there are new sources of risk including: Terrorism, pandemics and increasing major chance of catastrophe. Catastrophes happen more often and they are more expensive than ever. Many companies that operate in global markets rely on supply chains that may be compromised by unforeseen events. Acts of terrorism target business with the hopes of disrupting business enterprise on a wide scale. The threat of terrorism poses many risks to corporations and markets — many of which have little experience upon which to model potential risks. Because many of the threats facing businesses today are new and their potential impact is not well known, much new risk is not insurable. For example, there is no insurance available to protect a company against the loss of employees due to a pandemic. The best that traditional insurers can offer is worker compensation insurance that might cover part of the loss associated with a large-scale pandemic.

Insuring Against Pure Risk

At the same time that companies find that there is no insurance available to insure against some risks, insurers are also cutting capacity (of available insurance) and raising rates. The following example illustrates the challenges that face companies in adequately insuring against pure risks. Florida's Memorial Healthcare system was faced with the following scenarios in 2005 and 2006. The bullets represent: $ coverage, $ deducible and $ cost of premiums paid (Millman, 2007).

In 2005:

  • $1.2 billion in coverage
  • $60 million deductible
  • $4.5 million in premiums

In 2006:

  • $100 million in coverage
  • $100 million deductible
  • $12.5 million in premiums

To summarize, in 2006, Memorial healthcare was only able to secure 10% of its previous year's coverage, but that 10% cost three times the previous year's premiums. The result was that Memorial Healthcare opted to go without insurance coverage in 2006 because the insurance was no longer affordable. This "hard market" scenario is forcing companies to re-evaluate their risk management strategies, but some see a silver lining. In the case of Memorial Healthcare, the hospital decided to pool its risks with several other hospitals rather than have the traditional insurance industry handle the risk. This approach allows participants in similar industries to assess likely risks and focus on insuring against the most likely. This option offers specificity of risk coverage that might not be available from traditional insurers.

Self Insurance

The upside of corporations opting out of the tradition insurance market is that shareholders in public companies stand to do better from an investment standpoint. Because publicly-traded companies already trade their stocks in equity markets, they are well positioned to absorb potential risks. "Corporations can take on risks that individuals have a harder time managing" (Millman, 2007). Self insurance is not a new concept; most business and individuals accept some responsibility for self-insurance. The risk that businesses and individuals are willing to self-insure is typically defined as the premium's deductible. The term "retention" is the industry term for what the client is willing to pay out of pocket. The retention amount represents the maximum out of pocket "loss" that an individual or entity can incur that will not result in financial hardship (Okumura, 2007).

In the "text book" sense, an entity usually insures against large losses and self insures against small ones. From a statistical standpoint, small losses usually occur from common events and happen frequently and independently; so, the law of large numbers is applicable. Companies usually get their money's worth from insuring against small loses; insurers settle claims without dispute, pay on claims and even offer guidance about how to avoid future claims. In the case of oil giant British Petroleum (BP) the company has decided to buy insurance coverage for small events and self-insure for high impact risk events. The following points illustrate why this strategy is attractive to BP:

  • Equity in capital structure is a successful risk management technique.
  • BP can self-insure using its equity cushion.
  • BP has significant diversity in its operations, in-depth industry knowledge and the willingness to hedge against potential risks.


Today, one of the biggest challenges for insurers offering affordable coverage is that there's "no depth of actuarial records" for modeling catastrophic risk. The insurance industry must then rely on statistical modeling rather than actual historical records. In some cases, statistical models have proven wrong. For example, the models used in projecting losses for the 2004-2005 Atlantic Hurricane seasons grossly underestimated the cost of labor and...

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