Bill Black: How the “Super Crunchers” Became the “Super Torturers” of Finance Data

By Bill Black, the author of The Best Way to Rob a Bank is to Own One and an associate professor of economics and law at the University of Missouri-Kansas City. Originally published at New Economic Perspectives


Some books have spectacularly bad timing, like Moral Markets: The Critical Role of Values in the Economy, which was published in 2008 as a celebration of market and their nourishment of high ethical values. The book has many interesting chapters and I recommend it, but even lifelong market apologists now refer to the “corrupt culture of banking.” Ian Ayres, a brilliant professor of law and economics at Yale, published his book Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart to critical acclaim on August 28, 2007. Ayres’ book is an ode to how much better decision-making becomes when it is made empirically on the basis of very large data rather than through human judgment. There is a great deal of support in the literature for that thesis, and the result is one of the reasons why behavioral economics has become increasingly dominant. The general idea is that humans bring significant, unexamined biases to our decisions and that systems that rigorously examine the data are superior because they avoid these biases. That general idea continues to have considerable support and I have no personal problem with the general idea.

I write, however, to raise several cautions that arise from the disastrous performance of the Super Crunchers in finance during the financial crisis. Finance quants purported to be the best Super Crunchers in any commercial context. We are examining therefore a series of hundreds of catastrophic failures at our most elite financial institutions by those who claimed to be the best Super Crunchers in existence. (Physicists and the NSA’s top Super Crunchers always considered these claims to be laughable, but I will let them express that view.)

This article was prompted by reading a January 1, 2009 article entitled: “Irrational Expectations: How statistical thinking can lead us to better decisions” by “Deloitte University Press.” Deloitte, of course, is “talking its book,” trying to sell its consultants as Super Crunchers, but the article is lively and worth reading. The authors rightly consider the neoclassical model of decision-making a farce.

If you look at economics textbooks, you will learn that homo economicus can think like Albert Einstein, store as much memory as IBM’s Big Blue, and exercise the willpower of Mahatma Gandhi. Really. But the folks that we know are not like that. Real people have trouble with long division if they don’t have a calculator, sometimes forget their spouse’s birthday, and have a hangover on New Year’s Day. They are not homo economicus; they are homo sapiens.

Because they are, ultimately, quants incentivized to be sales guys, they oversell their quant products.

“But unlike a human decision-maker, a predictive model has the ability to optimally combine these and many other factors to efficiently estimate the employee’s relative likelihood of leaving. And unlike the human decision-maker, the predictive model will arrive at the same answer before and after lunch, takes virtually no time to draw conclusions, and is not affected by prejudices, pre-conceived ideas or cognitive biases. In short, predictive models can help us better approximate the ideally rational homo economicus.”

Here, two of the authors in Moral Markets could have helped protect the Deloitte authors from error. The ringing phrase in Moral Markets is that “homo economicus is a sociopath.” The Deloitte authors are businessmen who sell to other businessmen (and a very few women). They apparently think that homo economicus is superior to a human – “ideally rational” and not “affected by prejudices” – or love, empathy, mercy, justice, or Tikkun Olam, but they are in fact describing a sociopath. ..............(more)

http://www.nakedcapitalism.com/2015/04/bill-black-super-crunchers-became-super-torturers-finance-data.html