Other People's Money
So how is it that the smartest guys in the room lost all those trillions? In the early days of the disaster, they told us that it was because of the creation of ever more exotic financial instruments, but a hard look says that it's really quite simple: they borrowed a lot of money and lent it out to people who couldn't afford to pay them back. This is actually the Zeroth Law of Banking - when you lend money, try to make sure that it gets paid back.
I'm pretty sure that the wizards of Wall Street had actually heard of that concept. A banker who lends out his own money is very likely to pay a lot of attention to this principle, but all modern banks like to play at least partly with other people's money, which brings us to the First Law of Banking: borrow money cheap and lend it dear.
This first law can exert of whole lot of force when there happens to be a lot of money to be borrowed cheaply - the pressure to lend it dear can become quite irresistable. Now if you are playing with your own money you aren't too likely to forget that Zeroth Law, but suppose you are an executive of a corporation that does investment banking. Here, even the capital stock is somebody else's money. If you make a big profit, you become fabulously wealthy. If you screw up, you get fired, get a nice golden parachute, and wind up slightly less fabulously wealthy. How do you think that incentivises your behavior?
Ah, but all those brokerages and investment banks have sophisticated risk management tools to prevent disaster, right? Well, yes they do - but. Saul Hansell takes a hard look at how theses guys gamed their computers: How Wall Street Lied to Its Computers.
The people who ran the financial firms chose to program their risk-management systems with overly optimistic assumptions and to feed them oversimplified data. This kept them from sounding the alarm early enough.
Top bankers couldn’t simply ignore the computer models, because after the last round of big financial losses, regulators now require them to monitor their risk positions. Indeed, if the models say a firm’s risk has increased, the firm must either reduce its bets or set aside more capital as a cushion in case things go wrong.
Well worth reading. Maybe the real targets of all those hypercomplex financial instruments were the weaknesses in the computer progams supposed to manage the risks.
The ultimate point, though, is that corporations aren't likely to do a good job of managing other peoples money without somebody looking over their shoulders. I don't see an adequate substitute for intelligent and aggressive government regulation.