Interpretable Machine Learning

Since the global financial crisis, bank complexity has faced increasing scrutiny for its impact on financial stability, yet it remains difficult to measure. We introduce a novel explainable AI method to quantify complexity and find that it exhibits a pro-cyclical pattern, rising before crises and declining during periods of distress.