Next Year’s Model?

Some insurers reckon they can teach investment bankers a thing or two about handling risk.

With their snappy name and flashy mathematical formulae, “quants” were the stars of the finance show before the credit crisis erupted. Now the complex models of risk that they developed are accused of misleading banks about the safety of subprime-laced securities. Small wonder that investment bankers are working overtime to fix what went wrong.

One source of wisdom they may overlook is the staid world of insurance. After all, what could the green-eyeshade brigade of actuaries possibly teach the wizards of Wall Street? Several important lessons, reckon some insurers, who point out that much of their industry has thus far avoided the worst of the credit crisis.

Although a few firms—including Swiss Re, a big reinsurer due to report its 2007 results after The Economist went to press—face billions of dollars of write-downs on ill-judged involvement in America’s mortgage crisis, much of the European industry has so far come out relatively unscathed. Announcing a record profit for 2007 on February 25th, Munich Re, another big reinsurer, boasted it had just €340m ($514m) of subprime-related exposure, or less than 0.2% of its investments.

American insurers have a slightly bigger slug of subprime holdings than the Europeans, but analysts are sanguine. Fitch, a rating agency, notes that America’s life-insurance industry could probably weather $7 billion-8 billion of unrealised losses, though damage on such a scale would harm some firms.

This is a very different story from the bursting of the dotcom bubble. Back then, returns on insurers’ equity portfolios plunged just as liabilities on everything from life policies with guaranteed pay-outs to directors-and-officers (D&O) insurance soared, almost bringing the industry to its knees. Banks fared far better.

So what can banks learn from the insurers now the boot is on the other foot? Raj Singh, a former investment banker who recently became chief risk officer of Swiss Re, points out that the banks’ risk models, which try to put a value on how much they should realistically expect to lose in the 99% of the time that passes for normality, draw on reams of historical data. But this can produce a false sense of security.

Insurers looking at, say, catastrophe risks have relatively few data points and thus tend to have a healthy scepticism of models. They more often brainstorm their own scenarios. “In insurance, we have to think the unthinkable all the time,” says Mr Singh, pointing out that the industry came up with a scenario of a multiple plane crash above a metropolitan area well before the attacks on New York’s World Trade Centre in 2001.

Scenario-building usually involves insurers’ senior managers, whereas in many banks the “stress testing” of risk models is the preserve of quants. Moreover, in banks different teams often track different risks, masking potentially catastrophic correlations between them. Smart insurers are increasingly aware of the way in which life, property, business interruption and other risks interact—a portfolio risk-management approach encouraged by both regulators and investors.


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