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The Once and Future C&F
EPILOGUE Looking Ahead
D riving a bus by looking through the rearview mirror will only get you so far. Still, the rearview mirror is there for a reason. C&F’s story is interesting as a particular reflection of the broader insurance market over the centuries. But what does it mean to us today? Let’s go back to the questions I posed in the Introduction. 1. Could they have known? There is an unknowable element to the insurance business. There are corners we just can’t see around. There is no way that Bobby Russell could have foreseen that we would still be paying out asbestos claims 40 years after he left the company. Having said that, asbestos claims were not C&F’s only problem. Many of C&F’s issues were definitely knowable; the warning signs were there, if management had paid attention. Even if C&F’s problems were not entirely avoidable, early recognition and prudent action could have blunted the impact. The unknowables do exist, which makes it that much more important to line up the odds in our favor and do everything right in the “knowable” category.
2. Surely that couldn’t happen today, right? I can hear you thinking, “Those historical fools! That can’t happen to us. We have actuaries, and models — and actuaries with models!” In the battle between chaos and resilience, sometimes chaos will get the upper hand. We exist as an industry to absorb the volatility when that happens. We need to respect the sources of that chaos — the asymmetrical risks: new technology, new theories of liability, climate change, artificial intelligence, cybercrime, unanticipated aggregations, political upheaval, changes in public sentiment. We also have to respect the time lags involved. A big component of the problem with the 1980s liability crisis was the large lag between losses occurring and claims being reported. The claims incurred over decades showed up in a big wave. The industry was only able to shut the barn door after the horses were long gone. Chaos does not necessarily have to respect the models. Models make us feel better and are useful tools to put parameters around known issues. But many of them still rely on rearview-mirror thinking — and thus have a hard time handling time lags and inflection points. They would not have foreseen
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