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The Failure of Risk Management by Douglas W. Hubbard

This article was inspired by Douglas W. Hubbard's The Failure of Risk Management . If you enjoy this article then consider purchasing or borrowing the book.

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How to be a Successful Risk Manager

“A risk manager should always assume the list of considered risks, no matter how extensive, is incomplete.”

Risks cannot be fully managed when faulty models keep managers from foreseeing them. Unlike scientists, risk managers often lack the skepticism and mastery of statistics to accurately predict risk. The 2008 financial crisis occurred because the “experts” thought it was impossible. Rather than using current flawed models, question the effectiveness of your firm’s risk management practices.

Don’t solely rely on gut intuition or the recommendations of outside consultants. Forms of scoring risk can be skewed or biased. Probabilities and statistics are constantly improving and may best serve if used properly.

The four following strategies are often used to lessen the risks:

  1. “Avoid” – While refusing to take risks sidesteps some problems, it can create even more in the long-term. To be successful every business has to take risks at some point.
  2. “Reduce” – Investing in safety programs can mitigate damage if it ever arises.
  3. “Transfer” – From strategic language in your contracts to insurance, you can eliminate risk by assigning it to someone else.
  4. “Accept” – Sometimes it is necessary to take on risk and go about your day.

While types of risk managers range from actuaries to economists, “seven challenges” face risk management as a whole:

  1. “Confusion regarding the concept of risk” – The terms “risk” and “uncertainty” do not mean the same thing. An uncertainty, such as the type of weather you may have on a given day, does not correlate to a loss of money if things go south, whereas risk does.
  2. “Completely avoidable human errors in subjective judgments” – Biases and math errors occur when people apply gut feelings to the cold hard facts of probabilities. When of the most detrimental human errors is “overconfidence.” You must realize that a success which you can’t replicate was probably the result of random chance than your own abilities. Don’t lie to yourself and consider that the models you use to predict and manage risk may not be the best.
  3. “Entirely ineffectual but popular subjective scoring methods” – Rather than relying on subjective employee surveys or other scales that use relative scales to rank degrees of risk, focus on measurable “actual magnitudes” of risk.
  4. “Misconceptions that block the use of better, existing methods” – Don’t convince yourself that your situation is too specific for other methods to measure.
  5. “Recurring errors” – Avoid looking for small risks while ignoring the big ones. Investigate the effectiveness of your models through “back-testing.”
  6. “Institutional factors” – A common problem with risk management is that institutions isolate their risk managers. Companies will improve when they better communicate with their professionals.
  7. “Unproductive incentive structures” – Though executives may not be immediately rewarded for successful risk management, firms shouldn’t use the same systems if they don’t work.

While it is impossible to create a perfect model, you should approach risk management with the same skepticism as a scientist, ever improving your work.


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