mkurman Overview
ChainLadder implements actuarial reserve estimation methods for property & casualty insurance. Use it for loss reserving, claims triangles, and actuarial modeling in Python.
Installation
uv pip install chainladder
Basic Triangle and Reserve
import chainladder as cl
# Load sample auto liability triangle
tri = cl.load_dataset("RAA")
print(tri)
# Select development pattern
dev = cl.Development().fit_transform(tri)
# Run chain ladder method
model = cl.ChainLadder().fit(dev)
print(model.reserve_)
print(model.ldf_) # age-to-age factors
Mack Bootstrap
# Estimate reserve variability
mack = cl.MackChainLadder().fit(dev)
print(mack.reserve_)
print(f"CV: {mack.reserve_.std() / mack.reserve_.sum():.2%}")
print(mack.conditional_standard_error_)
Bornhuetter-Ferguson
bf = cl.BornhuetterFerguson().fit(dev)
print(bf.reserve_)
print(bf.expected_loss_) # a priori expected loss