Banks apply machine learning to CCAR models

Banks apply machine learning to CCAR models - Risk.net

Banks are increasingly seeking to apply machine-learning techniques to the models they use for regulatory stress tests. Machine-learning algorithms - designed to quickly make sense of large, unstructured datasets - are already used by banks to validate the models built for the US Federal Reserve's Comprehensive Capital Analysis and Review (CCAR).

Banks are increasingly seeking to apply machine-learning techniques to the models they use for regulatory stress tests. Machine-learning algorithms - designed to quickly make sense of large, unstructured datasets - are already used by banks to validate the models built for the US Federal Reserve's Comprehensive Capital Analysis and Review (CCAR).