Regulators wary of machine learning in bank models
Banks acknowledge they “cannot hide behind a complex tool” to assess interconnectedness
US regulators are raising concerns about the use of machine learning techniques to assess contagion risks in bank model networks.
Last year, certain entities supervised by the Federal Reserve were asked to analyse their aggregate model risk – essentially the interactions and dependencies between various risk and pricing models. Banks responded by experimenting with advanced computational techniques to understand model interconnectedness, including machine learning, network theory and
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