Consider the following:

• Catastrophe models often have come up short in the past (including for the events cited above), which has led to rollouts of new versions with much higher parameters.
• Do estimates of probable maximum losses for a 1-in-100-year or a 1-in-500-year return period really stand up to scrutiny when there is simply not enough historical data to support them? Furthermore, in light of how unpredictable nature has been in recent years, is the past a truly reliable guide to the future?
• Except for possibly extreme tail events that featured into very few strategic considerations, ESGs did not "predict" a stock-market crash of the magnitude caused by the 2008 global financial crisis.

So, if risk models have proven inexact in the past, where does this leave insurers?

A small handful of forward-thinking management teams fully appreciate the inherent uncertainty in a risk-taking industry—including in terms of more "known" risks, emerging risks and (sometimes very) ambiguous threats. They seek to mitigate (or reinsure or otherwise hedge) their concentrations and maximize upside potential via more insightful and comprehensive risk management than their peers. This way of managing risk is a highly complex and demanding discipline, and is very difficult for siloed organizations such as insurance companies to achieve.

Insurers at all stages of risk-management maturity can derive some of the benefits of such an approach by proxy, through understanding and reporting regularly on the estimated financial impact of various stresses across different aspects of their business. These might include the following (severity will differ from company to company):

• Stock market crashes of 600 to 1,000 points on the S&P 500 Index.
• Haircuts on Eurozone sovereign debt of up to 50 percent (or even more).
• Inflation—potentially driven by rising commodity prices—reaching between 7.5 percent and 15 percent per annum.
• Many economic commentators think that the potential collapse of the Euro could be even more cataclysmic than the events of 2008. If the Euro does fail, then the likely resulting failure of one or more systemically important financial institutions is likely to cause at least a credit and liquidity crunch on the scale of 2008.
• The failure of one or more major reinsurers could decimate the value of reinsurance assets.
• Economic losses on the scale of (1) the 2011 Thai floods in other emerging markets, (2) the 2011 magnitude 9.0 Japan earthquake in other quake-prone regions, (3) out-sized typhoons, or (4) extreme and prolonged hurricane/monsoon conditions. Potential scenarios might consider areas where extensive manufacturing capabilities have been outsourced, particularly in the high technology and industrial sectors, or where there are call centers for a wide range of global enterprises.
• Mega D&O claims triggered by another corporate failure on the scale of Enron or a Madoff-type scenario could affect a wide variety of financial institutions, professional advisers, and legal and accounting firms.

Once insurers analyze the risk scenarios like the ones we list above, they then can assess modeled losses in the context of current risk appetites, capital and liquidity assumptions/protocols, reinsurance strategies, and hedging strategies. The enterprise-wide insights they gain from analyses like these could be significant—and could lead to the design of governance actions that help safeguard the financial viability of a firm during times of abnormal distress. Documenting such insights and activities can go a long way toward the achievement of an ORSA's desired objectives. Accordingly, risk-based business activities can help facilitate regulatory compliance, which is very important in an increasingly regulation-based global economy.