Dodd and AIG Scratch Each Other's Back

The Hartford Currant has documented Connecticut Senator Christopher Dodd's flip-flop on the AIG bonuses, but it seems that there is more going on than he's addressed.

On Tuesday, Dodd said that he was not a member of the conference committee that crafted the final compromise bill and said that the exception had not been in the bill as he drafted it.

But late Wednesday, Dodd admitted in an interview with CNN that he had been involved in the change.

"I agreed reluctantly," Dodd said. "I was changing the amendment because others were insistent."

Don't think that Dodd is at an arm's length relationship with the financial services conglomerate. If you check the record of donations to him, you quickly see that AIG was his fourth largest contributor from 2003 to 2008, with a total of $223,478 donated.

The total money he raised during that time was $8,938,003. That means that AIG was directly responsible for 2.5 percent of all the money he raised during that period. The insurance industry was one of his top five industry donors with a total of $1,440,422, making AIG responsible for 15.5 percent of all insurance company donations to Dodd.

It's not surprising that Dodd has close ties to financial services as he's chair of the Senate's Banking, Housing, and Urban Affairs Committee. This is clearer when you add the total of campaign money received from 2003 to 2008 from securities and investments, insurance, and commercial banks: $6,588,012, or 73.7 percent of all campaign contributions to the senator.

It's not that the money comes directly from the companies, because that would violate election laws. However, 71% of the money comes from individuals; organizations like OpenSecrets.org collect the public information and then cross reference to find the totals. It seems pretty hard to believe that Dodd's own office wouldn't have made the same calculations.

Wall Street and the Wages of Estimation

Last week, the New York Times blog Bits had a piece about Wall Street analysts "lying" to their computers. Written by a journalist who has covered both the Internet and trading and finance, it indicates how little many reporters know about the mathematical processes they write about -- otherwise there might have been much earlier warnings of the problems now facing the world's economy.

Yes, the current meltdown is supposed to be a "once in a hundred years" event, as the president of a consulting firm told the reporter. However, these black swan events, when considered together, happen far more frequently than every hundred years. That's because when you have potential events that are independent of each other, but still capable of creating financial cataclysm, the cchance of at least one of them happening is the sum of the separate chances of a given one happening.

So already experience and math suggest that the surprise at an unusual event should have the same tone as Captain Renault being "shocked, shocked" at the gambling at Rick's in Casablanca. The concept of adding probabilities for independent events has literally become math in grade school, or at least high school.

Now for the other revelation:

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.

In other words, the computer is supposed to monitor the temperature of the party and drain the punch bowl as things get hot. And just as drunken revelers may want to put the thermostat in the freezer, Wall Street executives had lots of incentives to make sure their risk systems didn’t see much risk.

I'm sure there's something to this, but let us get at a more fundamental issue: many complex problems in math and engineering and science are too tough to easily solve. What people do, then, is simplify. You put the world into models and approximations that you have a prayer of solving. You drop factors that seem tiny in comparison with the rest of the problem in an attempt to simplify the equations even more. You employ numeric methods to get closer and closer to the "real" answer ... as close as you need.

Unfortunately, your answer is simply an approximation, nothing more. It may be acceptible for your uses if the real world conditions are forgiving enough. But when things get hairy -- you're trying to predict the behavior of materials in the face of quantum mechanics effects or trying to understand how an incredibly complex system, such as the weather or global finance, will behave -- then approximate may not be good enough. If a chip fails, well, you head back to the drafting board. When an economy fails, then you end up with huge banks and investment companies going out of business, oil prices swinging by $25 in a single day as short-sellers have to cover their positions, and governments begging for the right to spend $700 billion of taxpayer money to get their croneys out of the frying pan.