ReserveLab uses reinforcement learning to automate and augment P&C loss reserve calculations — from chain-ladder parametrisation to stochastic cashflow profiles — for global insurers and reinsurers.
Whether you want full automation or prefer to stay in control, ReserveLab has a product for your workflow.
A reinforcement learning agent that autonomously selects reserving methods, parametrises development factors, fits tail curves, and produces a fully documented reserve estimate — ready for actuarial sign-off.
An interactive dashboard where actuaries set parameters themselves — with the RL agent as a second opinion, formal diagnostic checks at every step, and professional reporting output.
The ReserveLab platform is built from modular open-source components — available on PyPI for the actuarial community.
ReserveLab is currently in development. Join the waitlist to get early access, updates, and be part of shaping the product.
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