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The Federal Reserve and Office of the Comptroller of the Currency guidance SR Letter 11-7 (link resides outside IBM) defines a model as "…a quantitative method, system, or approach that applies statistical, economic, financial, or mathematical theories, techniques, and assumptions to process input data into quantitative estimates."
Model risk can occur when a model is used to predict and measure quantitative information but the model performs inadequately. Poor model performance can lead to adverse outcomes and result in substantial operational losses. Implementing model risk management in a modern information architecture helps you:
How to build responsible AI at scale
Announcing the launch of watsonx.ai - The all new enterprise studio that brings together traditional machine learning along with new generative AI capabilities powered by foundation models
Enhance model compliance with custom tests and thresholds.
Listen to AI experts discuss digitization of governance in the age of AI.