The Data Conundrum for Risk Modelers

The Data Conundrum for Risk Modelers

Article Tony Hughes, 

Forecasts, scenario projections and other types of model output are not data. They are subject to error and potential bias, and risk managers would do well to keep this in mind when they are validating models.

Risk modelers today face a myriad of challenges, ranging from scenario analysis to forecasting to validation. But when modelers use a loose definition of the term “data,” bad habits can form quickly, creating problems they must understand and protect against.

If you research the etymology of "data," you will find that its original meaning is closely tied to the concept of a fact, something that is known or generally assumed to be true.

In modern times, however, usage of the word has expanded to include pretty much anything that can be stored in a spreadsheet. Forecasts and scenario projections are often referred to as "data," and I've even seen output from Monte Carlo simulations described in the same way. I suspect this is because computer scientists define the term very broadly to include anything that can be stored on a server.

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