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Communications of the ACM

Editor's letter

The Financial Meltdown and Computing

Communications Editor-in-Chief Moshe Y. Vardi

Many reasons have been offered for the near-collapse of the global economy: Alan Greenspan kept interest rates too low too long, greedy lenders pushed subprime loans on unqualified borrowers, and so on. A common thread to these explanations is that our financial system harbored a systemic risk that evaded attention until it was too late. From the perspective of computing professionals, the crisis was caused by "them," and we are its hapless victims. I'd like to offer here another explanation. I think information technology played a major role in the crisis.

The latest financial crisis is the third in the last 25 years. In Oct. 1987, stock markets around the world crashed. That crisis was blamed on program trading, which is trading driven by computer programs, implementing arbitrage and portfolio-insurance strategies. Ten years later, the Asian Financial Crisis hit mostly Asian markets, but led to the bailout of Long-Term Capital Management, a large U.S. hedge fund, whose arbitrage strategies threatened the stability of the U.S. financial market. No other period has witnessed financial crises with such frequency. A common thread to these disasters is that our financial system has reached a level of complexity that makes it opaque even to the "high priests" of finance.

You may recall the "computer-productivity paradox" of the late 1980s and early 1990s, referring to the gap between the level of investment in information technology and the slow growth of productivity. I always thought that discussions of this "paradox" often miss an important point. To assess the value of information technology to the economy, one must contemplate how the economy would have fared without it. The obvious answer is that today's complex economic world would simply be infeasible without information technology.

In his 1986 book, The Control Revolution: Technological and Economic Origins of the Information Society, James Beniger showed how the introduction of railroads and the telegraph in the 19th century enabled the growing complexity of the economy. JoAnne Yates described the intimate connection between information technology and economic complexity in her 1989 book, Control through Communication: The Rise of System in American Management. Modern technology has enhanced this trend to the point that Bruce Lindsay, a well-known IBM database researcher, recently quipped that "relational databases form the bedrock of Western civilization." Indeed, if a massive electromagnetic pulse wiped out our computing infrastructure, our society would face a catastrophic collapse.

Information technology has enabled the development of a global financial system of incredible sophistication. At the same time, it has enabled the development of a global financial system of such complexity that our ability to comprehend it and assess risk, both localized and systemic, is severely limited. Financial-oversight reform is now a topic of great discussion. The focus of these talks is primarily over the structure and authority of regulatory agencies. Little attention has been given to what I consider a key issue—the opaqueness of our financial system—which is driven by its fantastic complexity. The problem is not a lack of models. To the contrary, the proliferation of models may have created an illusion of understanding and control, as is argued in a recent report titled "The Financial Crisis and the Systemic Failure of Academic Economics."

The question for computing as a discipline is whether we have something to contribute to this discussion. Our technology has enabled the development of this highly complex system, but can it help penetrate this complexity? Can we build computational models for the global financial system that would help us understand rather than obscure its behavior? Most importantly, I believe, we must understand that technology has societal consequences; it played a key role in creating the mess we are in. It is not only "them," it is also "us."


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Alexandre Dulaunoy

Regarding computational model helping to understand the financial model, the Gaussian copula function is a notorious example of a misinterpreted function to analyze risks in credit.

For more information about the function and the effect in the financial sector :

Sometimes we, as researcher, tend to minimize the potential misuse of our research works and publications and prefer to focus on their positive use. It's somehow our duty to analyze the potential abuse that can be performed against our researches (and not only in information security...).

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