Banks are doubling down on the use of machine learning techniques for model validation in the face of regulatory scepticism over ‘black box’ models.
Machine learning has allowed banks to slash the amount of time and resources they dedicate to complying with SR 11-7, the model risk management framework issued by US prudential regulators in 2011.
The guidance ushered in a stricter era of model governance, formally separating first-line model development and second-line validation teams and
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