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Innovation & Growth Initiative: Montgomery County Benchmark
Learn about Abington's Next Century. To access a white paper that compares Abington to the rest of Montgomery County, click here >
Join us at
Sat. Nov. 16
9:00 AM to Noon
Celebrate our efforts to raise money to plant new trees in Jackson Park. Learn about our ideas to rid the park of invasive vines. Learn More >
Report on Financial Crisis
Federal Report Sheds Light on Causes of Meltdown of Global Economy
The Financial Crisis Inquiry Commission examined the financial and economic crisis that has gripped our country and has attempted to explain its causes. They highlight nine conclusions throughout the report. First, they concluded that this financial crisis was avoidable. Second, the Commission found that widespread failures in financial regulation and supervision proved devastating to the stability of the nation’s financial markets. Third, they observed dramatic failures of corporate governance and risk management at many systemically important financial institutions were a key cause of this crisis. Fourth, the body found that a combination of excessive borrowing, risky investments, and lack of transparency put the financial system on a collision course with crisis. Fifth, they noted that the government was ill prepared for the crisis, and its inconsistent response added to the uncertainty and panic in the financial markets. Sixth, the Commission concluded that there was a systemic breakdown in accountability and ethics. Seventh, they studied collapsing mortgage-lending standards and the mortgage securitization pipeline lit and spread the flame of contagion and crisis. Eight, over-the-counter derivatives contributed significantly to this crisis. And finally, ninth, the report concludes that the failures of credit rating agencies were essential cogs in the wheel of financial destruction.
The seventh item, which focuses on collapsing mortgage standards, is a mult-faceted problem that was exacerbated by the fact that mortgage brokers had no accountability to banks, yet banks would bundle mortgages into pools of mortgage-backed securities and other investment instruments. The failure to collect accurate information on borrowers at the very beginning of the loan origination process was magnified as many mortgages (whose borrowers represented high-levels of risk) were bundled into instruments that were characterized as safe and low-risk. The Report can be downloaded here.
In 2007, Massachusetts Institute of Technology (MIT) had already identified a flaw in the way data was gathered and maintained, but financial institutions were not inclined to change what was working. In MIT Sloan Research Paper No. 4672-07, authors Nicolas Prat and Stuart Madnick concluded that data quality and believability are crucial for operational efficiency and sound decisions in any organization or system. They ground their approach on "provenance metadata", i.e. the origin and subsequent processing history of data. The approach is structured into three increasingly complex building blocks: (1) definition of metrics for assessing the believability of data sources, (2) definition of metrics for assessing the believability of data resulting from one process run and (3) assessment of believability based on all the sources and processing history of data. The MIT paper can be downloaded here.
This model would have avoided many of the problems as mortgages were sold and bundled. It would have forced institutions to authenticate the information, assess the quality and history of the loan origination officer and maintain provenance metadata on each loan as it moved through the system.
Another flaw in the system revolved around macro-modelling that relied on the flawed data about buyers and false assumptions about markets. Wired Magazine reported that Chinese math genius David X. Li developed a formula called Gaussian copula function, which was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. It was based on the concept of probability, but had one fatal flaw: It relied on historic housing valuation data over a relatively short period. In other words, it did not look back 100 years to see how housing prices fluctate or how interest rates, money supply or inventory impact that fluctuation. Therefore, the flawed model assumed that prices would continue to rise as it had over the brief period in the model.
The combination of flawed data about homeowners who took out mortgages and a flawed model that assessed risk through rose-colored glasses were major contributing factors to the meltdown in domestic housing and the global economic crisis.
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