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Is Big Data a Big Problem for Analytic Models?

In today’s battle for organizations to turn Big Data into faster, smarter and more compliant decisions, a simple statistic tells the story of why this isn’t so easy. It is estimated that most businesses are only able to derive real value from approximately 12% of the data available to them (source: Forrester Research). A lot of effort is being put into combing through the immense variety and volume of data sources and types to separate the “wheat from the chaff” – or what data is noise, vs. what can drive analytic insights and actions.

For banks and other institutions, the problem of Big Data adds to an already precarious balancing act between getting more analytic models into production to address a widening spectrum of business challenges, and ensuring these models retain sharpness over time. Even if an organization solves the daunting challenge of finding the occasional needle in the Big Data haystack, there is considerable pressure on analytic modelers to figure out how to put this data to use.

And let’s face it: a bank or insurer group may have hundreds, even thousands, of models at work across its business lines and regions – many crucial to the organization’s profitability and risk exposure. As the use of predictive and other models proliferates, however, only a small percentage of these businesses have instituted structured programs of model management to determine whether their critical models are remaining current and valid in setting the parameters of risk control decisions and identifying profitability opportunities.

With big data straining the model management foundation even further, organizations are faced with hiring new analytic talent to meet the demand for better, faster model development, which may not be possible due to budgetary restrictions or the increasing scarcity of such resources. Even then, there’s no guarantee their modeling infrastructure can stand up to regulatory scrutiny, help identify model degradation, or deploy new models on a timely basis.

It’s for these reasons that FICO has just announced FICO® Model Central 5.0™, our analytic technology solution that dramatically increases visibility into and control over the analytic models that drive better decision outcomes across any enterprise.

Model Central is an end-to-end solution for complete model management and governance, allowing organizations to know the status of models at all times, while making sharper predictions to drive better decisions. The solution also streamlines workflow management, helping reduce go-live cycles and – particularly critical for those organizations trying to embed Big Data into their decision cycles – allowing for rapid model updates to reflect game-changing analytic insights.

For organizations seeking to evolve model management, compliance and governance from art to science – while helping ensure valuable Big Data discoveries don’t get lost in a maelstrom of other priorities – FICO Model Central can help.

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