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Synthetic Data and the Model Risk Committee

How do you validate a model trained on data that never happened?

By Sarah Lindqvist

Synthetic Data and the Model Risk Committee

Model risk frameworks were written for logistic regressions with twelve features. They are being applied, more or less unchanged, to systems with billions of parameters.

Explain the model, said the framework. The framework did not anticipate this.

The committees that adapted did so by shifting from explaining the model to constraining its inputs and monitoring its outputs. It is less satisfying and considerably more practical.

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