Casualty catastrophes have become increasingly frequent and severe over the past decade, exposing (re)insurers to much more risk than they may realize. One root cause can trigger a chain reaction that can bleed balance sheets and even imperil solvency. Until recently, casualty carriers had little choice but to accept this risk. The maturation of Enterprise Risk Management (ERM) practice and the development of new casualty-specific catastrophe models, though, signal a change. The more complex the casualty risks and regulations carriers face, the more they are recognizing that improving their ERM practices could yield competitive advantage. Now, it is possible to make the accumulation of casualty risks both knowable and manageable. As casualty catastrophes become more common, carriers will be able to take informed action to protect their capital.
Casualty Catastrophes, Frequent and Severe
Property catastrophes are utterly familiar. The same exposures generally can be found in the same regions. Little changes from one year to the next. As a result, property (re)insurers have access to a considerable amount of historical data, which is evident in the sophistication and utility of the models at their disposal. Unfortunately, casualty (re)insurers do not have access to information of this depth. The historical record is thin and constantly changing. The variables almost seem infinite, making it almost impossible to identify, model, and evaluate a large set of scenarios.
The “casualty catastrophe” is perhaps the most daunting threat that casualty (re)insurers face today. One root cause has the potential to trigger a chain reaction of liability through a web of tightly intertwined business relationships. The proliferation of liability is replicated in casualty (re)insurance portfolios, leading to the possibility of unexpectedly high claims, a drain on capital, and, in the extreme, risk to a firm’s solvency. Multiple lines of business and insureds are swept up in a casualty catastrophe, and the carriers involved may have to pay claims that seem unrelated to the event’s initial trigger.
Casualty catastrophe occurrences have become increasingly common over the past decade. The current financial catastrophe is the easiest to cite, due to its sheer size and the fact that it is still unfolding. But, there have been many others. The collapse of the “dotcom economy” led to scandals around initial public offering (IPO) laddering and equity analyst conflicts of interest. Accounting firms were not alone in suffering financial loss related to such debacles as Enron, WorldCom, Tyco, and Adelphia. While insured losses did not reach those of property catastrophes, economic damages were profound. Enron’s loss of USD66 billion in market capitalization alone — not including the economic damage caused to other companies — was more than double that of Hurricane Ike (approximately USD30 billion). The financial catastrophe in progress now is estimated to have caused economic damage of above USD1 trillion, with more likely to follow.
Casualty catastrophes, unfortunately, do not follow patterns — unlike property catastrophes. The geographies, natural conditions, and other indicators of hurricanes, earthquakes and other property disasters offer some sense of predictability. A hurricane on the Florida coast is not unusual. Casualty catastrophes, however, rarely arise from the same conditions - or in the same companies or industries – as their predecessors. In fact, many casualty catastrophes are “black swans,” at least to the insurers that cover them. They appear out of nowhere and wreak havoc quickly.
Just about every large public or private company and its service providers (e.g., investment banks, law firms, accountants, and consultants), strategic partners, and supply chain participants is a potential flashpoint. The data set is vast, and when casualty catastrophe indicators appear, it is typically too late to take preventive action. Therefore, casualty writers need to be proactive in regards to the unknown, as difficult as that may seem.
Uncertainty is always a factor in insurance risk and capital management decision-making. Targeted, supported assumptions applied to available data using thoroughly researched and carefully designed models are intended to counteract the unknown, at least to the extent possible. Thus, to protect their capital from the casualty catastrophe risk, carriers have needed a tool that can probe a portfolio to apply potential disaster scenarios, identify likely exposures and map how liability would spread from the root cause to other industries, geographic jurisdictions, and lines of business. Not only has the technology been difficult to develop, it has tended to conflict with the prevailing practice of siloed risk management.
This is the first in a six-part series. To have the next installment delivered directly to your inbox, register for e-mail updates.