A motivation for Injsurance Linked Securities (ILS)
Insurance companies are in the business of assuming risks from individuals or companies. They manage those risks by diversifying over a large number of policies, perils and geographic regions. A particularly difficult problem is the management of risk from high severity, low probability events (catastrophe risk, or “CAT” risk), such as that posed by major earthquakes or hurricanes. The risk from low severity, high probability events (for example, auto collision or medical insurance) can be diversified by writing a large number of similar policies. Suppose that the insurer charges a premium equal to the expected average annual loss and has a very large number of policies. By the law of large numbers, it can expect to pay out approximately this amount in claims in each year. It then can earn a stable profit on the investment income from the premiums. But the law of large numbers breaks down when confronted by infrequent and severe catastrophe risks — losses can occur across an entire pool of policies simultaneously.
An important tool to manage catastrophe risk is reinsurance. Reinsurance is the means by which insurance companies transfer their own portfolio risk to other reinsurance companies. In the late 1980s and early 1990s, several large losses from U.S. catastrophes (Hurricanes Hugo and Andrew, and the Northridge earthquake) put large strains on the capacities of the reinsurance markets (estimated to total $50–100 billion). Although the situation has eased in the last few years, prices in the reinsurance market remain very volatile and could potentially increase again, perhaps significantly, after one or more major future catastrophes.
Innovative mechanisms have been developed in recent years to stabilize pricing and coverage
by transferring risk, in security or derivative form, into the much larger pools of investment capital available in global capital markets. Since catastrophe risk is inherently uncorrelated with financial markets, such instruments are potentially attractive to many types of investors. Thus, an integration of the reinsurance and the capital marketscan be mutually beneficial for both insurers and investors,providing insurers with reinsurance coverage at reasonable and stable prices, and offering attractive securities to investors.
ILS Structure
1. A special purpose vehicle (SPV) is created
- provides reinsurance to a ceding insurance (or reinsurance) company
- issues securities to investors
2. SPV collects funding for the interest payments the investors receive via:
2. a) SPV collects funds from the investors, which are deposited in a trust.
2. b) Cedant (the insured) pays a premium to the SPV in exchange for the reinsurance that the SPV underwrites.
3. Payout
3. a) Loss doesn't occur or doesn't exceed pre-defined trigger => investors receive back their principal at maturity. Cedant gets nothing.
3. b) Loss above the attachment point (trigger) of the reinsurance contract occurs => funds are used first to make payments to the ceding company under the agreement, leading to a partial or total lossof principal to the investors.
Contract Structure:
1. index-based - loss 'trigger' based on an index (for example, of industry loss experience). Easier for investors to analyze the risk (no need to understand the details of the cedant’s business/underwriting quality). However, index-based introduces basis risk exposure for cedant (occuring if cedant exposure differs from that of the index used to determine the payoff of the contract; in which case, payoff may not fully cover loss).
2. indemnity-based - loss 'trigger' based on the actual loss experience of the
cedant’s own book of business, closely resembles a traditional reinsurance program.
3. parametric structure - loss 'trigger' based on the physical parameters of the natural hazard, such as the magnitude and location of an earthquake.
http://property-casualty.com/News/2010/7/Pages/Ala-Uses-Parametric-Cover-For-SIF-Hurricane-Exposure.aspx
Assessing Cat Risk
The underlying peril risk must be quantified in order to price an ILS. Various cat modeling firms employ an approach combining the use of historical data with certain parametric assumptions. We can estimate potential modern-day effects of historical storms, given today’s buildings and insurance policies. This leaves us with various problems related to the limited size of the sample of historical events (“tail problem”). This problem can be attenuated by making parametric assumptions about the probability distribution of the characteristics of the cat event, creating "stochastic storms".
From Peril Model to Financial Loss
