FT.com / Weekend / Reportage - Genesis of the debt disaster: In the 1990s, a young team at Wall Street investment bank JP Morgan pioneered a new way of making money – credit derivatives. Within a decade, the market for these exotic securities had exploded to more than $12,000bn – and some people later blamed them for fuelling the global financial fiasco. In the first of two extracts from her book, Fool’s Gold, the FT’s Gillian Tett reveals how the innovation genie was first let out of the bottle – and eventually devoured the system, to the horror of its creators. The first sign that there might be a structural problem with the innovative bundles of credit derivatives that bankers at JP Morgan had dreamed up emerged in the second half of 1998. In the preceding months, Blythe Masters and Bill Demchak – key members of JP Morgan’s credit derivatives team – had been pestering financial regulators. They believed that by using the new credit derivative products they had helped create, JP Morgan could better manage the risks in its portfolio of loans to companies, and thereby reduce the amount of capital it needed to put aside to cover possible defaults. The question was by how much. (Though these bundles of credit derivatives later went under other names, such as collateralised debt obligations [CDOs], at that time these pioneering structures were known as “Bistro” deals, short for Broad Index Secured Trust Offering). Masters and Demchak had done the first couple of Bistro deals on behalf of their own bank without knowing the answer to their question for sure. But when they were doing these deals for other banks, the question of reserve capital became more important – the others were mainly interested in cutting their reserve requirements.
The regulators weren’t sure. When officials at the Office of the Comptroller of the Currency and the Federal Reserve had first heard about credit derivatives and CDOs, they had warmed to the idea that banks were trying to manage their risk. But they were also uneasy because the new derivatives didn’t fit neatly under any existing regulations. And they were particularly uncertain over what to make of the unusually low level of capital available to cover losses on the derivatives.
When the team did their first Bistro deal, they pooled more than 300 of JP Morgan’s loans, worth a total of $9.7bn, and issued securities based on the income streams from these loans. The lure of the idea was clear: the team had calculated that they only needed to set aside $700m – a strikingly small sum – against the risk of defaults among the 300-plus loans. After much debate, the credit rating agencies had agreed with the team’s assessment of the risks, and the deal had gone ahead on the basis that if financial Armageddon wiped out the $700m funding cushion, JP Morgan would absorb the additional losses itself. To Masters and Demchak, the chance that losses would ever eat through $700m were minuscule.
That argument didn’t wash with European regulators, and some of their US counterparts were uneasy, too. Christine Cumming, a senior Fed official, indicated to Masters and Demchak that JP Morgan should look for a way to insure the rest of the risk – the “missing” $9bn in their original Bistro scheme – if the bank wanted to gain approval to cut its capital reserves. So Masters and her team set out to find a solution. They started by giving the bundle of “uninsured” risk a name. Masters liked to refer to it as “more than triple-A”, since it was deemed even safer than triple A-rated securities. But that was too clumsy to market, so they came up with “super-senior”. The next step was to explore who, if anyone, might want to buy or insure it.
The task did not look easy. As far as JP Morgan was concerned, this risk was not really risky at all, so there was no point paying anything other than a token amount to insure it. On top of that, whoever stepped up to acquire or insure the super-senior risk had to be brave enough to step into an unfamiliar world.
The seeds of AIG’s destruction
Masters eventually spotted one solution to the super-senior headache. In the past, one of JP Morgan’s longstanding blue-chip clients had been the mighty insurance company American International Group. Like JP Morgan, AIG was a pillar of the American financial establishment. It had risen to prominence by building a formidable franchise in the Asian markets during the early-20th century. That business was later extended to the US, making the company a powerful force in the American economy after the second world war. AIG was considered a weighty and utterly reliable market player, and like JP Morgan, it basked in the sun of a triple-A credit rating.
But within AIG, an upstart entrepreneurial subsidiary was booming. In the late 1980s the company hired a group of traders who had previously worked for Drexel Burnham Lambert, the infamous – and now defunct – champion of the junk-bond business under Michael Milken in the mid-1980s. These traders had developed a capital markets business, known as AIG Financial Products and based in London, where the regulatory regime was less restrictive. It was run by Joseph Cassano, a tough-talking trader from Brooklyn. Cassano was creative, bold and highly ambitious. More important, he knew that, as an insurance company, AIG was not subject to the same burdensome rules on capital reserves as banks. That meant it would not need to set aside anything but a tiny sliver of capital – at most – if it insured the super-senior risk. Nor was the insurer likely to face hard questions from its own regulators because AIG Financial Products had largely fallen through the cracks of oversight. It was regulated by the US Office for Thrift Supervision, whose officials had scant expertise in the field of cutting-edge financial products.
Masters pitched to Cassano that AIG take over JP Morgan’s super-senior risk, and Cassano happily agreed. It was a “watershed” event, or so Cassano later observed. “JP Morgan came to us, who were somebody we worked with a great deal, and asked us to participate in some of what they called Bistro trades [which] were the precursors to what [became] the CDO market,” he explained. It seemed good business for AIG.
AIG would earn a relatively paltry fee for providing this service – just 0.02 cents per dollar insured per year. But if 0.02 cents is multiplied a few billion times, it adds up to an appreciable income stream, particularly if no reserves are required to cover the risk. Once again, the magic of derivatives had produced a “win–win” solution. Only many years later did it become clear that Cassano’s trade had set AIG on the path to ruin.
With the AIG deal in hand, the JP Morgan team returned to the regulators and pointed out that a way had been found to remove the rest of the credit risk from their Bistro deals. They started plotting other sales of super-senior risk to other insurance and reinsurance companies, which snapped it up, not just from JP Morgan but from other banks too.
Then, ironically, just as this business was taking off, the US regulators weighed in again. Officials at the Office of the Comptroller of the Currency and the Fed indicated to JP Morgan that after due reflection they thought that banks did not need to remove super-senior risk from their books after all. The lobbying by Masters and others had seemingly paid off. The regulators were not willing to let the banks get off scot-free. If they held the super-senior risk on their books, they would need to post reserves one-fifth the size of the usual amount (20 per cent of 8 per cent, meaning $1.60 for every $100 that lay on the books). There were also some conditions. Banks could only cut their capital reserves in this way if they could prove that the risk of default on the super-senior portion of the deals was truly negligible, and if the securities being issued via a Bistro-style structure carried a triple A credit rating from a “nationally recognised credit rating agency”. Those were strict terms, but JP Morgan was meeting them.
The implications were huge. Banks had typically been forced to hold $800m reserves for every $10bn of corporate loans on their books. Now that sum could fall to just $160m. The Bistro concept had pulled off a dance around the international banking rules.
For a while, Demchak’s team stopped transferring super-senior risk from JP Morgan’s books. But then Demchak became uneasy. The super-senior risk was ballooning to a staggering figure, because when the bank arranged these credit derivatives transactions for clients, it typically put the super-senior risk in the deal on its own balance sheet. In theory, there was no reason to worry. But by 1999, the total pipeline of future deals had swelled towards $100bn. Something about that mountain of risk started to offend Demchak’s common sense. “If you have got $60bn, $100bn or however many billions of something on your balance sheet, that is a very big number,” he remarked to his team. “I don’t think you should ignore a big number, no matter what it is.”
The problem with correlation
Demchak was acutely aware that modelling the risks involved in credit derivatives deals had its limits. One of the trickiest problems revolved around the issue of “correlation”, or the degree to which defaults in any given pool of loans might be interconnected. Trying to predict correlation is a little like working out how many apples in a bag might go rotten. If you watch what happens to hundreds of different disconnected apples over several weeks, you might guess the chance that one apple might go rotten – or not. But what if they are sitting in a bag together? If one apple goes mouldy, will that make the others rot too? If so, how many and how fast?
Similar doubts dogged the corporate world. JP Morgan statisticians knew that company debt defaults are connected. If a car company goes into default, its suppliers may go bust, too. Conversely, if a big retailer collapses, other retail groups may benefit. Correlations could go both ways, and working out how they might develop among any basket of companies is fiendishly complex. So what the statisticians did, essentially, was to study past correlations in corporate default and equity prices and program their models to assume the same pattern in the present. This assumption wasn’t deemed particularly risky, as corporate defaults were rare, at least in the pool of companies that JP Morgan was dealing with. When Moody’s had done its own modelling of the basket of companies in the first Bistro deal, for example, it had predicted that just 0.82 per cent of the companies would default each year. If those defaults were uncorrelated, or just slightly correlated, then the chance of defaults occurring on 10 per cent of the pool – the amount that might eat up the $700m of capital raised to cover losses – was tiny. That was why JP Morgan could declare super-senior risk so safe, and why Moody’s had rated so many of these securities triple-A.
The fact was, however, that the assumption about correlation was just that: guesswork. And Demchak and his colleagues knew perfectly well that if the correlation rate ever turned out to be appreciably higher than the statisticians had assumed, serious losses might result. What if a situation transpired in which, when a few companies defaulted, numerous others followed? The number of defaults required to set off such a chain reaction was a vexing unknown. Demchak had never seen it happen, and the odds seemed extremely long, but even if there was just a minute chance of such a scenario, he didn’t want to find himself sitting on $100bn of assets that could conceivably go bust. So he decided to play it safe, and told his team to look for ways to cut their super-senior liabilities again, irrespective of what the regulators were saying.
That stance cost JP Morgan a fair amount of money, because it had to pay AIG and others to insure the super-senior risk, and those fees rose steadily as the decade wore on. In the first such deals with AIG, the fee had been just 0.02 cents for every dollar of risk insured each year. By 1999, the price was nearer 0.11 cents per dollar. But Demchak was determined that the team must be prudent.
The mortgage time bomb
Around the same time, the JP Morgan team stumbled on a second, potentially bigger problem. As the innovation cycle turned and earnings declined from the early Bistro deals based on pools of corporate loans, Demchak asked his team to explore new uses for Bistro-style deals, either by modifying the structure or by putting new kinds of loans or other assets into the mix. They decided to experiment with mortgages. Terri Duhon was at the heart of the endeavour. Only 10 years earlier, Duhon had been a high-school student in Louisiana. When she told her relatives she was going to work in a bank, they had assumed she was going to be a teller. Now she was managing tens of billions of dollars. She was trained as a mathematician, and she thrived on adrenaline, riding motorbikes in her spare time. Even so, she found the thought of being in charge of all those zeros awe-inspiring. “It was just an extraordinary, intense experience,” she later recalled.
A year after Duhon took on the post, she got word that Bayerische Landesbank, a large German bank, wanted to use the credit derivatives structure to remove the risk from $14bn of US mortgage loans it had extended. She debated with her team whether to accept the assignment; working with mortgage debt wasn’t a natural move for JP Morgan. But Duhon knew that some of the bank’s rivals were starting to conduct credit derivatives deals with mortgage risk, so the team decided to take it on.
As soon as Duhon talked to the quantitative analysts, she encountered a problem. When JP Morgan had offered the first Bistro deals in late 1997, it had access to extensive data about all the loans it had pooled together. So did the investors who bought the resulting credit derivatives, since the bank had deliberately named all of the 307 companies whose loans were included. In addition, many of these companies had been in business for decades, so extensive data were available on how they had performed over many business cycles. That gave JP Morgan’s statisticians, and investors, great confidence in predicting the likelihood of defaults. But the mortgage world was very different. For one thing, when banks sold bundles of mortgage loans to outside investors, they almost never revealed the names and credit histories of the individual borrowers. Worse, when Duhon went looking for data to track mortgage defaults over several business cycles, she discovered it was in short supply.
While America’s corporate world had suffered several booms and recessions in the later 20th century, the housing market had followed a steady path of growth. Some specific regions had suffered downturns: prices in Texas, for example, fell during the Savings and Loans debacle of the late 1980s. But since the second world war, there had never been a nationwide house-price slump. The last time house prices had fallen significantly en masse, in fact, was way back in the 1930s, during the Great Depression. The lack of data made Duhon nervous. When bankers assembled models to predict defaults, they wanted data on what normally happened in both booms and busts. Without that, it was impossible to know whether defaults tended to be correlated or not, in what circumstances they were isolated to particular urban centres or regions, and when they might go national. Duhon could see no way to obtain such information for mortgages. That meant she would either have to rely on data from just one region and extrapolate it across the US, or make even more assumptions than normal about how defaults were correlated. She discussed what to do with Krishna Varikooty and the other quantitative experts. Varikooty was renowned on the team for taking a sober approach to risk. He was a stickler for detail and that scrupulousness sometimes infuriated colleagues who were itching to make deals. But Demchak always defended Varikooty. His judgment on the mortgage debt was clear: he could not see a way to track the potential correlation of defaults with any confidence. Without that, he declared, no precise estimate could be made of the risks of default in a pool of mortgages. If defaults on mortgages were uncorrelated, then the Bistro structure should be safe for mortgage risk, but if they were highly correlated, it might be catastrophically dangerous. Nobody could know.
Duhon and her colleagues were reluctant simply to turn down Bayerische Landesbank’s request. The German bank was keen to go ahead, even after the uncertainty in the modelling was explained, and so Duhon came up with the best estimates she could to structure the deal. To cope with the uncertainties the team stipulated that a bigger-than-normal funding cushion be raised, which made the deal less lucrative for JP Morgan. The bank also hedged its risk. That was the only prudent thing to do, and Duhon couldn’t see herself doing many more such deals. Mortgage risk was just too uncharted. “We just could not get comfortable,” Masters later said.
In subsequent months, Duhon heard through the grapevine that other banks were starting to do credit derivatives deals with mortgage debt, and she wondered how they had coped with the lack of data that so worried her and Varikooty. Had they found a better way to track the correlation issue? Did they have more experience of dealing with mortgages? She had no way of finding out. Because the credit derivatives market was unregulated, details of the deals weren’t available.
The team at JP Morgan did only one more Bistro deal with mortgage debt, a few months later, worth $10bn. Then, as other banks ramped up their mortgage-backed business, JP Morgan largely dropped out. Eight years later, the unquantified mortgage risk that had frightened off Duhon, Varikooty and the JP Morgan team had reached vast proportions. And it was spread throughout the western world’s financial system.