Actuarial loss modeling in Python: severity, frequency, aggregate loss, fitted distributions, and insurance loss analytics.

Monte Carlo simulation of insurance losses using a frequency–severity model with Poisson claim frequency, lognormal and gamma severity distributions, and tail risk analysis.

Open-source actuarial tooling for Python: experience analysis, pricing/rating, loss modeling, risk simulation, and tail-risk methods.