The ERM Current™

An article in this week’s edition of The New York Times Magazine entitled “Risk Mismanagement” provided a view into the use of statistical models in the world’s largest financial institutions to understand risk.  Value at Risk (“VaR”) models are the focus of the article and are criticized for not predicting rare, catastrophic events (known as Black Swans) such as the financial crisis that we have experienced.  

At the height of the bubble, there was so much money to be made that any firm that pulled back because it was nervous about risk would forsake huge short-term gains and lose out to less cautious rivals. The fact that VaR didn’t measure the possibility of an extreme event was a blessing to the executives.  It made black swans all the easier to ignore.  All the incentives — profits, compensation, glory, even job security — went in the direction of taking on more and more risk, even if you half suspected it would end badly. 

While the VaR models are not perfect, they should not shoulder the blame for the mismanagement of risk.  The mismangement of risk was driven by short-term decision making and pure greed.

If you have been following The ERM Current™ over the past few weeks, you will probably recall discussions about systemic risk permeating the financial markets.  Well, yesterday the Wall Street Journal chronicled the making of the engine that fueled the systemic risk.  Much of the credit derivative problem emanated from AIG and their use of sophisticated computer models to value the risk within each of their financial products. An academic consultant from Yale University promoted these models and was paid handsomely for it.  His name is Gary Gorton and here is what he had to say just last month.

“You have this very, very complicated chain of the movement of the risk, which made it very opaque about where the risk finally resided. And it ended up residing in many places. So the whole infrastructure of the financial market became kind of infected, because nobody knew exactly where the risk was.” 

The primary objective of these financial products was to be “opaque” so investors would unwittingly buy into the scheme.  However, when the institutions who peddled these products placed their faith in the computer models to value the risks, their fate was sealed.