Peggy Brinkman, a principal actuary at Milliman, maps the trajectory: from univariate actuarial techniques, through generalized linear models, to gradient boosted machine models, and now to explainable boosting machines – a class of model that delivers gradient boosting accuracy with the interpretability that state regulators require for rate filing approval. The shift is happening across the industry, but at very different speeds. “New modeling techniques can extract more value from the same data in terms of risk understanding,” Brinkman said. “Advances in methodologies are as important as bringing in new data sources.”
Inside the AI modeling race reshaping catastrophe risk
