In fact, some machine learning models are fully “interpretable” and therefore may lend themselves to a broader array of use cases. By “interpretable” I mean that developers can “look under the hood” to see how those models make their predictions or classifications, similar to traditional models.
In this regard, we welcome a recent initiative from the European Securities and Markets Authority to draw up guidelines for credit rating agencies to disclose whether and how ESG factors are reflected in their ratings.