The Failure of Risk Management: Why It's Broken and How to Fix It

CHAPTER 9

Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models

There is perhaps no beguilement more insidious and dangerous than an elaborate and elegant mathematical process built upon unfortified premises.

 

—THOMAS C. CHAMBERLAIN, GEOLOGIST (1899)

 

 

When it comes to improving risk management, I’m an unrepentant bigot for quantitative methods in the assessment, mitigation, or deliberate selection of risks for the right opportunities. I think the solution to fixing many of the problems we’ve identified in risk management will be found in the use of more quantitative methods—but with one important caveat. In everything I’ve written so far, I’ve promoted the idea that risk management methods should be subjected to scientifically sound testing methods. We should hold even the most “quantitative” models to that same rigor. They get no special treatment because they simply seem more mathematical or were once developed and used by highly regarded scientists.

The idea that the mere use of very sophisticated-looking mathematical models must automatically be right has been called crackpot rigor and a risk manager should always be on guard against that. Unfortunately, the rapid growth in use of sophisticated tools has, in many cases, outpaced the growth in the skills to use these tools and the use of questionable “quantitative” methods seems to be growing out of hand.

I’m a fan of science and scientific method. But science has evolved to its current advanced ...