Machine Learning Model Risk Management with Wells Fargo

Agus Sudjianto, EVP, Head of Corporate Model Risk, Wells Fargo
Abstract:
All models are wrong and when they are wrong they create financial or non-financial risks. Understanding, testing and managing model failures are the key focus of model risk management particularly model validation. For machine learning models, particular attention is made on how to manage model fairness, explainability, robustness and change control. In this presentation, I will focus the discussion on machine learning explainability and robustness, particularly how to develop fundamentally interpretable models through architecture constraints including deep learning.
Ai4 is industry’s leading artificial intelligence conference. Join our next event: ai4.io

[@htoolay6581]

Thank you so much. This is what I'm looking for.

[@pt3931]

Great !

[@NestorNarvaez]

Very interesting

[@psychogalvanometer8945]

Does that mean AI models will replace traditional statistical models one day?