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Code to rate tail risk (cat) using 100 years of public data. Using pandas, MC simulations, and classification/regression models, this hybrid quant/ml model suits various insurance risks (tail risk) with publicly available data. Vectorization of categorical features could improve loss ratios, outperforming GLMs. No actuaries needed!