Stochastic Dual Dynamic Programming (SDDP) can solve large multistage financial problems, but its implementation complexity has kept it out of practitioners’ reach. We show how the open-source Julia package SDDP.jl helps remove this barrier. We start with goal-based asset allocation, where dynamic policies track user-defined synthetic indexes under Markovian economic regimes. We extend this framework to asset-liability management for insurers, jointly deciding investments, exposure, reinsurance and debt under solvency constraints. We derive intuitive and risk-aware solutions for up to 30-years instances. A short intraday foreign-exchange application further illustrates the tool’s flexibility.