Reimagining Model Risk Management: New Tools and Approaches for a New Era
A collaborative report by Chartis and Evalueserve.
Anna Slodka-Turner –
More on Model risk management
Is more data, and less math, a good thing in modern models?
Now that Big Data is mainstream, model developers face an epistemic trade-off: enable models to make more accurate predictions by loosening traditional statistical methodologies. But what impact might this have on the future accountability of our…
Breaking the glass box: achieving ‘explainability’ that actually explains
Tied to the growing popularity of machine learning (ML) tools is the need to explain their underlying rationale. But buzzwords, like ‘glass box’, are steering the explainability conversation off course. Meanwhile, without proper investment in the tech innovations and governance methods to properly validate ML, it could proliferate throughout the financial industry without the necessary safeguards.