07 Dec The subprime mortgage mess: A case of subprime data?
Subprime mortgages – loans made to more risky buyers often with less than favorable terms – are the scapegoat du jour around the world, as companies take write-downs and turn in poor results citing exposure to the subprime market as a primary cause.
Investors and armchair quarterbacks wonder how everyone from banks to retailers could have underestimated the risks this market presented, as loans were made with little to no oversight, and estimations of risk ranged from slightly optimistic to wildly overzealous.
As fingers are pointed in the search to who was responsible, one cannot help but wonder if IT could have played a role in mitigating the impact of subprime exposure. For the last several decades data warehouses have been in vogue. Acting as massive, consolidated repositories of corporate data, they supposedly aggregate diverse data and allow for detailed analysis. The financial industry, often the industry with the highest IT spend, is rife with data warehouses, and IT in most mature companies has long been gathering and storing everything from customer data to industry trends.
Mission not accomplished
Where IT has fallen down is in actually leveraging this data. Like the eccentric art collector who buys priceless works only to crate them and lock them away in a dark safe never to be viewed by human eyes, IT has grown obsessed with data collection in the name of business intelligence. Rather than determining key trends to analyze, or metrics that might help mitigate risk exposure, IT has long neglected the intelligence component of business intelligence. IT focused on data collection, with companies bragging about the size of their data warehouses while bad bets on the subprime market erased billion of dollars of assets nearly overnight.
Business intelligence is yet another area where IT shops and their CIOs have taken a solution approach – in the case of subprime exposure, to the peril of the company as a whole. By purchasing a business intelligence “solution” and quickly loading it with reams of data, CIOs assumed they could “check the box” on business intelligence, when all they had really done was build a repository. Similar to the notion of learning through osmosis, CIOs assumed that building the repository would miraculously bring about more robust analytical capabilities and insight into future trends.
The subprime mess is a fine example of the morass engendered by a solution mindset. Very few factors precipitated the crisis, primarily poor assumptions about the risk level of loan recipients, and a reliance on someone else to determine the aggregate risk of thousands of these loans repackaged into an investment vehicle. The primary causes of the financial crisis were certainly not rocket science, and the data required to make a more informed decision were readily available. In essence, companies outsourced doing their homework on risk exposure to rating agencies.
While CIOs frequently pontificate on risk and chasing hackers and viruses, they missed their chance to analyze readily available data about subprime loans, and perhaps raise the red flags about their riskiness far in advance of the current financial meltdown.
Would you rather have rolled out a bold new policy forcing mind-numbingly esoteric password requirements on your internal users, or identified that several billion dollars of company assets represented far more risk than was originally assumed?
Previous articles by Patrick Gray
• Patrick Gray: Project management: Pay the toll and save the day
• Patrick Gray: Demolishing the antiquated IT customer-service model
• Patrick Gray: Supercharge business value with breakthrough IT
• Patrick Gray: Death by deliverables a project management pitfall
• Patrick Gray: With tech implementations, it’s NOT the methodology, stupid
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