I.O.U.: Why Everyone Owes Everyone and No One Can Pay Summary

John Lanchester

Chapter 1 Summary

John Lanchester begins I.O.U.: Why Everyone Owes Everyone and No One Can Pay by admitting that as a child he was scared of ATM machines. Looking back, he now realizes, he may have been on to something. He explains that the frictionless way money moves around the world can be frightening. Few people can really conceptualize the numbers involved in the global economy. What is the difference between a million seconds and a billion seconds? It is the difference between roughly twelve days and thirty-two years. By the end of 2008, Icelanders went to their ATMs and discovered that the frictionless withdrawal of money was no longer frictionless. Their banks, which had twelve times as many assets as their national economy, had failed. Lanchester seeks to explain how the “Reykjavíkization of the world economy” came about.

Lanchester tracks the process back to the fall of the Berlin Wall. Until that point, Western liberal democracies had an ideological counterpoint, and though Lanchester maintains that the Western liberal democracies are the most admirable societies humanity has ever seen, they are admirable in part because they sought to show that they provided citizens with a better standard of living than their Communist adversaries. Therefore, the “jet engine” of capitalism remained hitched to the “oxcart” of equality and fairness. With the defeat of the Soviets, the capitalists were under less pressure to provide equality and fairness. Consequently, previous bans on torture were lifted, the income for the middle class remained stagnant, and the income gap between the super rich and everyone else grew. A mystical faith in capitalism became normal, and the financial sector’s wealth skyrocketed. Unfortunately, notes Lanchester, the victory party following the fall of the Berlin Wall was neither fair nor sustainable.

Oddly, few people are able to explain how the financial sector works, even though banks are essential to the system everyone lives in. Banks are machines for making money. They take in money, lend some of it at interest, and when they collect their money, they have more money, which means that they can lend more. Lanchester explains that a bank’s balance sheet differs from other balance sheets because a bank increases its assets by lending credit to others. During the 1990s and 2000s, bankers began to lend credit to anyone, increasing the banks assets and the bankers’ bonuses. Additionally, many banks began to over-leverage their assets. When it turned out that many of those assets would not be recovered (known as toxic assets), the banks suddenly became insolvent and were bailed out by taxpayers.

Lanchester explains that now no one knows which banks are actually solvent. They do not lend credit because they are waiting for their toxic assets to regain value. However, a bank that cannot lend credit is useless. It becomes a “zombie bank.” An economy with zombie banks will grind to a halt because there is no machine for making money.

Chapter 2 Summary

Banking should be simple: banks take in money, which they lend out at interest. The bank must reduce risk by lending only to reputable customers. However, during the 20th century, banking became modern, which means that it became self-referential, abstract, and separated from common sense. The arrival of modernism in finance was the management of chance and risk. Lanchester illustrates by explaining the financial instruments called derivatives.

Say a farmer agrees to sell his or her crop ahead of harvest for an agreed upon price. That contract can then be bought and sold; it is a derivative because its value derives from the crop. The simplest derivatives are options and futures. An option is the right, but not the obligation, to buy or sell something in the future for a specified price. A future carries the obligation and is therefore riskier. Lanchester explains that someone might spend $500 on an option to buy a sports car for $50,000 in a year’s time. If the price goes up, the option has gained value and is a good investment. If the market value of that car drops, then the option was not a good investment and the buyer can decide not to buy the car. He or she loses the $500 option, or “premium.”

The derivative market opened when when Fischer Black and Myron Scholes worked out how to price derivatives. Lanchester explains that the value of the total market in derivatives is thought to exceed the world’s economic output by about $66 trillion, or by roughly tenfold. Lanchester explains that in an ideal world, derivatives would be used to reduce risk. An investor can choose to buy wheat but can also buy options that allow him or her to sell it at a fixed price. This is “hedging.” However, confident financial experts often buy options—or better yet, futures, since although these carry greater risk they also carry greater reward—that align with their primary investments. This magnifies risk.

Credit default...

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Chapter 3 Summary

Lanchester turns his attention to the housing market. He begins by discussing interest rates and mortgages. Because America and the U.K. promote policies that will allow people to buy houses, the laws allow banks to give credit with few restrictions. In Germany, a person can only borrow up to 60% of a property’s value, and in France people can only borrow up to a third of their monthly pay. This means that in America and the United Kingdom, people are often in debt well beyond their income. America and the U.K. may share the prioritization of the citizen owning property, but there are differences. In the U.K., a mortgage’s interest rate shifts, and it is the mortgager that takes on the risk that interest rates will go up. In America, banks tend to offer fixed interest mortgages, which means that the bank takes on the risk that interest rates will go up. In America, the banks that were designed to carry these risks were Fannie Mae and Freddie Mac. The costs of these risks swamped both banks.

The push for everyone to own property led to policies that encouraged banks to lend money to people that could not pay back their loans. The Depository Institutions Deregulation and Monetary Control Act, for example, allowed banks to charge higher rates and fees to some borrowers—in other words, it legalized subprime loans. The Alternative Mortgage Transaction Parity Act of 1982 legalized variable interest rates, and it allowed for “balloon payments” to catch up the unpaid balance at the end of a loan. The Tax Reform Act of 1986 allowed for a tax deduction of interest on mortgage loans, which increased their attractiveness as a form of debt. The goals of these policies were continued under Presidents Clinton and Bush, and by 2005, home ownership was nearly 70%. The gap between ethnic minorities and the white population had also narrowed.

Normally, a bubble bursts of its own accord due to inflation and interest rates. To explain this,...

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Chapter 4 Summary

Mortgages were attractive to investors at the start of the twenty-first century. Stocks and bonds were unattractive, but property prices were rising quickly. Homeowners pay higher interest rates than governments and companies, which means that mortgages would offer more money. Further, many people were waiting to buy property. Given that J.P. Morgan had already worked out a way to engineer risk out of their balance sheets through collateralized debt obligations (CDOs) with respect to bonds, the lenders felt that they were taking on no risk when they lent money. 

At first, mortgage-backed CDOs were only used with “conforming” mortgages. These were mortgages that conformed to the rules of Freddie Mac and Fannie Mae: Freddie Mac and Fannie Mae lend to financial institutions that own the mortgages rather than to the general public. “Nonconforming” mortgages had been carefully extended to what the Clinton Administration had called the “underserved” communities—lower income and higher risk groups—and the policy had appeared successful. The number of these “nonconforming” mortgages quickly grew. They were also known as “subprime mortgages.” These subprime mortgages may have been riskier, but this higher risk meant they were potentially more lucrative. Still, as yet, no one had worked out a way to design CDOs based on subprime mortgages.

Most mortgages that are made with reliable borrowers are easy to model. However, because the market for subprime mortgages was new, there was no data from which lenders could model and predict risk. David X. Li came up with a way to use a Gaussian copula function to create subprime mortgage CDOs. CDO and CDS (credit default swap) markets skyrocketed. The lender now had no need to bother about whether the borrower could pay. The banks went on to create pools of structured debt that were tranched for investors. The banks then created structured investment vehicles, part-independent subsidiaries of the banks that kept assets off of the banks’ balance sheets. This allowed the banks to avoid the Basel restrictions on capital reserves. Although J.P. Morgan had created the CDS industry, they did not buy join invest in the mortgage-backed CDOs. Unfortunately, many other banks did. 

Lanchester explains that the “circuit breaker of risk assessment” was no longer in place at this point. Anyone could take out a mortgage, regardless of their credit history. Their debt would be bundled and sold. It led to an epidemic of “predatory lending,” overwhelmingly in the United States. The lending system became chronically prone to abuse, though many of these abuses were perfectly legal. Atrocious scams became commonplace. These banks had no stake in whether or not the borrowers could repay their loans, and so they adopted a “buyer beware” stance while many borrowers lied about their credit and income.

Chapter 5 Summary

Lanchester argues that the central mistake was how bankers calculated risk. In general, people are not good with risk. People do not tend to act rationally. Daniel Kahneman and Amos Tversky, two economists who studied heuristics, or the patterns of thinking that people use to interpret data, concluded that people’s heuristics are often wrong. Economists are unduly preoccupied with developing “pseudomathematical formulae” that predict behavior and decision-making. Traditionally, people tried to avoid risk through diversification, but today the industry relies on mathematical models like VAR, or “value at risk.” 

VAR is a statistical technique that arose in response to Black Monday, the 1987 stock crash. Dennis Weatherstone, the CEO of J.P. Morgan, initially adopted it, and he would receive a VAR report every day at 4:15. VAR’s job was to summarize the risk the bank took that day. VAR is made up of three parts: a time frame, a number stating the amount of money at risk, and a fixed probability expressing the chance that money will be lost. For example, a bank might have a 5% risk of losing $1 million over the next 24 hours. Lanchester notes that VAR explains the risk only within a given range of probabilities. Where does that range of probabilities come from? The data that VAR relied upon tended to perform well in response to “normal” market activity. However, it was a horrible predictor of catastrophe, or events that occur outside of the given range of probabilities plugged into the model.

Lanchester explains that bankers came to recklessly rely on VAR. The number became an industry standard, though it was never without detractors. When David X. Li released his Gaussian copula function to CDOs was adopted, it allowed the mortgage-backed CDOs market to be reduced to a number. Because there was no national housing market at that time, because there had never been a national downturn in the housing market, and because there was little data on subprime mortgages, Li’s formula ignored the absence of historical data and instead represented correlation based on the price of credit default swaps. Unfortunately, the data was rubbish.

The models tended to assign market crashes astoundingly low probabilities of occurring. Lanchester points out that common sense dictates that market crashes do happen, but according to the math, the Black Monday crash of 1987 was a 10 sigma event, which means that it was all but impossible. Common sense would tell someone that giving loans to people with lousy credit histories is doomed to fail. However, the mathematical calculation of risk that bankers relied on was suggesting that the mortgage market was as likely to crash as a person was to win the U.K. national lottery, consecutively, twenty-one times. Consequently, the bankers failed as “utterly and completely as it is possible to fail...They were exposed as doing something which was contrary to the nature of reality.”

Chapter 6 Summary

Lanchester explains that there were four factors that led to the financial crisis. There was a failure, a mistake, a problem, and a climate. Though many people failed to act responsibly, the regulators in particular failed to react to the financial crisis. The bankers, meanwhile, made a mistake when they began to rely exclusively on mathematical models of assessing risk. The problem was the subprime mortgages. However, none of it would have been possible if not for the financial climate.

Lanchester considers the failure of the regulators to act. There were many “funny smells” leading up to the crash, but the regulators did nothing to avert the crisis. The subprime loans, for example, were given the highest rating by...

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Chapter 7 Summary

Regardless of what caused the financial crisis, the taxpayer is responsible for a gigantic bill. Lanchester turns his attention to what the future holds, and it is grim. He suggests that the public has not even started to look at the bill yet. At the moment, the focus is on restarting growth. Once that starts, governments will need to raise taxes and increase interest rates to cover public debt. This will turn the private and public sector against each other since public and private layoffs will likely follow. How big is the bill? Lanchester relies on Barry Ritholtz’s analysis of the crisis when he explains that it is worth more than the combined cost of the Marshall Plan, the Louisiana Purchase, the Apollo moon landings, the...

(The entire section is 417 words.)