
For years, a fundamental tension has governed actuarial science, forcing insurers to choose between the raw predictive power of advanced analytics and the unyielding regulatory demand for transparent, explainable models. This article dissects the evolution from traditional modeling to automated solutions that promise a powerful synthesis of these competing needs. An exploration of legacy methods’ limitations reveals a new wave










