What is Model Explainability? And Why is it So Important?
Machine learning models are designed to predict event outcomes based on input data. As the scale of data increases, it becomes more and more difficult for humans to understand the logic behind a decision.
As research progresses, machine learning models become ever more complex, and play bigger roles in our financial lives, financial institutions will need to be able to honestly and transparently weigh the evidence behind any system’s predictions.