century tulip mania.
As we’ve witnessed on countless occasions, “this time is different” is only true if you don’t go back far enough.
Another reason why risk management did not in many cases achieve the desired results — that is, protecting firms from getting into serious trouble — stemmed from the strategies and tools that many depended on. In the years leading up to 2007 (as well as today), powerful technology and rocket-science analytics imbued the industry and those who regulate it with a false sense of confidence.
Although a tightly-structured, data-driven methodology seems like the best way — and to some, the only way — of generating an unbiased assessment of where things stand, it has serious shortcomings. Among other things, this approach fails to take account of the dark forces that come into play when risk management matters most — i.e., when the hurricane strikes.
Moreover, as is true with all attempts to quantify human behavior, real life tends to be more complicated than any model can handle. The upshot: such systems invariably incorporate guesswork and shortcuts. And yet, once the data goes through the mathematical meat-grinder, it assumes an air of infallible precision that is difficult to challenge, even with good old common sense and the wisdom of hard-knocks experience.
It is easy to lose sight of the bigger picture when the focus is on “the numbers.” A case in point: the curious notion that pyramiding risk exposure is somehow less dangerous when market volatility is decreasing, as some value-at-risk models would have us believe. Huh? Anybody who knows anything at all about real-world dynamics would challenge that assumption.
In fact, the proliferation of quantitatively-oriented methods of analyzing man-made activities brings to mind what I believe was another contributor to the crisis: an overreliance on systems and technology. When risk management is viewed as science, where complex algorithms, a hierarchy of rules, and textbook training dictate the best course of action, it’s pretty clear that insufficient allowance is being made for the human element.
This is not to say that all risk models are riddled with bad math or incomplete histories, or depend on inputs that are unproven or irrelevant to the situation at hand, as was all too often the case in the lead-up to the crisis. But even when the methodology has been carefully designed and each aspect dutifully tested, the fact is that mechanized approaches fail to account
for what behavioral economists long ago figured out.
People are, more often than not, irrational and unpredictable, and they make decisions that may or may not be to the advantage of themselves or others, including the firms they work for and society at large. Sometimes, the drivers will be economic incentives. At other times, the impetus to act will be the pull of the crowd. That means the true level of exposure might be far different than the theoretical value.
Can a data-driven approach take all of this into account? In a word, no. Hence, those who are tasked with managing risk need to learn as much as they can about the biggest creators (and abusers) of risk: people. They must spend time studying human psychology and understanding just how people think, interact with others and respond under pressure, especially when they are exposed to financial risk in one form or another.
One final key mistake that many risk managers made — both before and after the crisis erupted — was to direct the bulk of their attentions to the idiosyncratic exposure of the firms they worked for. As the crisis spread, what seemed to cause the most damage was not the fallout from the bad positions of any one operator, but the threat posed by the collective exposure of many different market participants.
Realistically speaking, the notion that an insular department or firm-centric approach can adequately measure just how exposed a business is to loss or ruin in a highly competitive, tightly-interconnected and increasingly complex world leaves much to be desired.
Although some firms might genuinely have believed they had matters under control when viewed in a relatively narrow context, it was often an illusion. In many cases, it was like putting out a fire in the yard as a blaze raged in the forest next door.
In the end, then, if there is one key takeaway from the events of the past several years, it is the idea that those who are charged with evaluating and managing risk exposure need to question each and every assumption. Among those they might want to begin with: Are traditional approaches to risk management the best way forward?
Michael J. Panzner is a 25-year veteran of the global stock, bond and currency markets who has worked at a variety of large financial services firms, including HSBC, Soros Funds, ABN Amro, Dresdner Bank and JPMorgan Chase. He is the author of When Giants Fall: An Economic Roadmap for the End of the American Era; Financial Armageddon: Protecting Your Future from Four Impending Catastrophes; and The New Laws of the Stock Market Jungle: An Insider’s Guide to Successful Investing in a Changing World. He can be reached at panzner@gmail.com.
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