All The Devils Are Here: Unmasking the Men Who Bankrupted the World (12 page)

Mostly, though, Fannie Mae made no apologies for its stance. “I used to say that the goal at Fannie was to have a seamless yes to anyone who wants to do anything for housing,” Johnson later said. “But we didn’t say yes to crap, to fraud. We were probing the boundaries, but it was carefully circumscribed.”

Says a former Fannie executive: “About 98 percent of our mortgages were done at market rates. We were giving away a little at the edge of the big machine.” This person adds: “Johnson’s attitude was, ‘I am not going to let the government define what affordable housing is to this company.’ ”

That would soon begin to change, however. In 1999, Andrew Cuomo, who had been appointed HUD secretary during Bill Clinton’s second term and was a true believer in affordable housing, proposed increasing the affordable housing goals. To an unusual degree, Cuomo was immune to Fannie’s charms and impervious to its threats. He’d already taken on Johnson on another issue, and did not back down when Fannie pushed back. In July 1999, the GSEs agreed that by 2001, 50 percent of the mortgages they guaranteed would be loans made to low- or middle-income Americans. One way the GSEs could meet those goals, of course, was by lowering their underwriting standards, just as the subprime industry had done. Indeed, the housers at Fannie had high hopes that their company could serve as the sheriff in the lawless world of subprime lending. An exhaustive study Fannie had done revealed that many subprime borrowers were so fearful of being rejected that they were willing to pay very high rates just to hear a yes. Some studies showed that plenty of subprime customers could have qualified for a prime loan—meaning they were paying far more for their mortgages than they had to. Fannie said it could use its clout to make sure that borrowers got a fair deal.

Later, many conservative critics of the GSEs would come to see this moment as the capitulation of Fannie and Freddie to the Clinton affordable housing drive. That wasn’t really true. The real reason Fannie was willing to
finally move into riskier territory was the same reason Countrywide did: profits. Subprime was taking off—and the GSEs were sitting on the sidelines. “Their motivation to enter this market is to continue a phenomenal record of amazing shareholder enrichment,” Anne Canfield, a longtime critic of the GSEs, wrote at the time. There was another potential issue, too. At a congressional hearing in June of 2000, the Reverend Graylan Scott Hagler of the Plymouth Congregational United Church of Christ, in Washington, D.C., who also claimed that the GSEs were entering the subprime business to “maximize returns,” said, “The real fear here is that when the economy goes south, or just through one of those cycles it periodically goes through, if Fannie and Freddie are engaged in these subprime markets, then they will get left holding the bag, and the American taxpayer with them.”

Says a former Fannie executive: “It met our business goals. You have to start there. All the criticisms about Fannie being too shareholder driven and too profit driven—they are true! Shareholders were an important constituency at Fannie. For the smart people we brought in, they were the only constituency.”

Still, Fannie moved cautiously. In 2000, it put out guidelines listing what sort of riskier loans it would buy; Cuomo used those guidelines in Fannie’s affordable housing goals. Under the new rules, certain kinds of high-risk loans, ones that consumer advocates felt took undue advantage of borrowers, wouldn’t count toward Fannie and Freddie’s affordable housing goals. There is no data to prove that the GSEs avoided those loans, although neither company ever guaranteed large quantities of loans that they considered subprime.

In the end, though, it didn’t really matter whether Fannie and Freddie moved into riskier mortgages quickly or slowly, reluctantly or gleefully. What mattered was that they entered this new market at all. In so doing, they gave their imprimatur to what had previously been an entirely separate universe. A line that had once been absolute was now blurring. “The whole definition of subprime was ‘the stuff that Fannie and Freddie wouldn’t touch,’ ” a former executive explains. No longer.

Much later, Maxwell would concede, with great sadness, that Fannie Mae had forgotten a simple question: Why are we here? If Fannie Mae had kept that question paramount, the company would have remembered that it didn’t exist solely to generate ever-increasing profits or to keep pace with the private market, but to supply liquidity when the housing market needed it. If Fannie had remembered that, the company might have found its moral compass when it needed it most—and maybe left a different legacy.

T
he most cutting-edge firm on Wall Street in the early 1990s was not Drexel Burnham Lambert, which had dominated the 1980s with its junk bonds, or Goldman Sachs, whose sheer moneymaking prowess would first dazzle and then repulse the country during this last decade. No, the firm that everyone on Wall Street wanted to emulate was a one-hundred-year-old commercial bank: J.P. Morgan. During the same era that the subprime mortgage industry was rising from the primordial ooze and Fannie Mae was consolidating its power over the mortgage securitization market, J.P. Morgan was making an important series of innovations around the concept of risk.

Risk was the bank’s obsession. It wanted to measure risk, model risk, and manage risk better than any institution had ever done before. It wanted to embrace certain risks that no bank had ever taken on, while shedding other risks that banks had always accepted as an unavoidable part of banking. To this end, J.P. Morgan (along with other firms, too) hired mathematicians and physicists—actual rocket scientists!—to create complex risk models and products. They were called “quants” because they tried to make money not by examining the fundamentals of stock and bonds, but by using more quantitative methods. They devised complex equations rooted in modern portfolio theory, which held as its core principle that diversification reduced risk. They searched for securities that seemed to move in tandem, and then used computers to take advantage of tiny discrepancies in their price movements. Their risk models were statistical marvels, based on probability theory. The new securities they invented, designed to shift risk from one firm’s books to another’s, were practically metaphysical. After the transaction was completed, the original security remained on the first firm’s books, but the
risk
it represented had moved. These new products were called derivatives, because
they were “derived” from another security. J.P. Morgan’s chief contribution in this area was something called the credit default swap. Its breakthrough risk model was called Value at Risk, or VaR. Both products quickly became tools that everyone on Wall Street relied on.

What did these innovations have to do with subprime mortgages? Nothing, at first. J.P. Morgan and Ameriquest could have been operating on different planets, so little did they have to do with each other. But in time, Wall Street realized that the same principles that underlay J.P. Morgan’s risk model could be adapted to bestow coveted triple-A ratings on large chunks of complex new products created out of subprime mortgages. Firms could use VaR to persuade regulators—and themselves—that they were taking on very little risk, even as they were loading up on subprime securities. And they could use credit default swaps to off-load their own subprime risks onto some other entity willing to accept it. By the early 2000s, these two worlds—subprime and quantitative finance—were completely intertwined.

Not that anyone at J.P. Morgan could see what was coming. Like Ranieri in the 1980s, the bank’s eager young innovators were convinced they were making the financial world a better, safer world. But they weren’t.

The chairman and CEO of J.P. Morgan in the early 1990s was a calm, unflappable British expatriate named Sir Dennis Weatherstone. Knighted in 1990, the year he took over the bank, Weatherstone had the bearing of a patrician despite working-class roots; his first job, at the age of sixteen, was as a bookkeeper in the London office of a firm J.P. Morgan would acquire. When he died in 2008 at the age of seventy-seven, an obituary writer described him as “dapper, precise, soft-spoken … unfailingly polite … a man no one disliked.”

He was also a new kind of bank CEO. He had never been a commercial banker. His career had been spent as a trader in London. His last big assignment before moving to New York to join the J.P. Morgan executive suite was as the head of the firm’s foreign currency exchange desk.

A reserved man who rarely granted interviews, Weatherstone was little known outside the banking industry. But his influence on J.P. Morgan—indeed, on banking itself—was profound. In the early 1980s, J.P. Morgan earned most of its money by making commercial loans. By 1993, nearly 75 percent of its revenues derived from investment banking fees and trading profits, the result of the bank moving to what one British journalist described as “new forms of finance.” The most important of these new forms was
derivatives. By 1994, the year Weatherstone retired,
Fortune
could quote a bank executive calling them “the basic business of banking.”

The essential purpose of derivatives has always been to swap one kind of risk for another; that’s why many common derivatives are called swaps. The earliest derivatives attempted to mitigate interest rate risk and currency risk. In the volatile economic environment of the 1980s, when interest rates and currency values could swing suddenly and unpredictably, big companies were desperate for ways to protect themselves; derivatives became the way. An interest rate swap allowed a company to lock in an interest rate and pay a fee to another entity—a counterparty, as they were called on Wall Street—willing to take the risk that rates would suddenly jump. (If rates dropped instead, the counterparty would make a nice profit.) The counterparty, in turn, would often want to hedge, or reduce, its own risks by entering into an offsetting trade with another entity. Which would then want to hedge
its
risks. And so on. Trading derivatives could often seem like standing between two mirrors and seeing the reflection of your reflection of your reflection, ad infinitum. Hedging derivative risk was a classic example of the old Wall Street saw that “trading begets trading.”

Given his background, it is no surprise that Weatherstone was a big believer in derivatives; as a currency trader, he had undoubtedly structured his share of swaps. He was also very clear-eyed about the need for J.P. Morgan to move away from commercial lending and into more profitable areas like trading and derivatives.

Thus, one of Weatherstone’s first acts when he became CEO in 1990 was to persuade the Federal Reserve to allow the bank to begin trading securities in the United States. This was a huge shift in U.S. policy; ever since the Great Depression, the government had kept commercial banking and investment banking apart. (Glass-Steagall, the 1933 law that mandated this change, forced J.P. Morgan to spin off its investment banking arm, which was rechristened Morgan Stanley.) In recent years, though, American banks had gotten back into the trading business, except that they did it from London instead of New York. Weatherstone argued that as banking changed, U.S. policy had to change, too, or it would risk losing its most profitable operations to the City of London. Though the Fed couldn’t overturn the law, it could interpret Glass-Steagall in a different, looser way. Which it did. Little noticed at the time, this reinterpretation marked the transformation of banking from a sleepy business to a cutthroat one. Now that banks had trading desks, there was both more money to be made—and more pressure to make it.

Having run a trading desk, Weatherstone also had a deep understanding of risk—which meant, among other things, that he was more aware than other bank CEOs of how much he
didn’t
know about the risks on J.P. Morgan’s books. It made him uncomfortable.

All of J.P. Morgan’s businesses had risks, whether it was buying or selling stocks and bonds, writing complex derivatives contracts, or making commercial loans to big companies. As head of the foreign currency exchange desk, Weatherstone had been attuned to all the risks in the portfolio he oversaw. But as CEO, he lacked the tools to get his arms around the various risks on the company’s books, much less understand how they related to each other. Did the risks taken on one desk nullify the risks being taken on another desk—or did they exacerbate them? Even before he’d become the bank’s CEO, Weatherstone decided that J.P. Morgan needed a new approach to risk.

The man he chose to lead this effort was a Swiss executive, Till Guldimann. Like Weatherstone, Guldimann had spent most of his career on trading desks. He, too, developed a keen interest in risk management, which he viewed as woefully unscientific. The traditional way of managing trading risks, for instance, was to impose a limit on how much capital a trader had at his disposal. But as a risk manager, Guldimann was often confronted with the problem of what to do when a trader wanted to increase his limit. “How should I know if he should get his increase?” Guldimann says. “All I could do is ask around. Is he a good guy? Does he know what he’s doing? It was ridiculous.”

There was never any question about how Guldimann and his team would approach this task. They would use statistics and probability theories that had long been popular on Wall Street. (The Black-Scholes formula, for example, developed in the early 1970s for pricing options, had become one of the linchpins of modern Wall Street.) The quants swarming Wall Street were all steeped in those theories—this was the essential building block of virtually everything they did. They knew no other way to approach the subject.

Sure enough, Value at Risk, or VaR, the model the J.P. Morgan quants came up with after years of trial and error, was built on a key tenet of the mathematics of probability, called Gaussian distribution. (It is named after Carl Friedrich Gauss, a German mathematician who introduced it in the early 1800s.) Its daunting name notwithstanding, the Gaussian distribution curve is something we’re all familiar with: it is a simple bell curve, which looks like this: