reinsurance.dev

Who this is for

This site is written for software engineers who are new to reinsurance: the backend engineer who has just joined a reinsurer with strong software skills and no insurance background, the senior engineer pivoting from fintech, the architect modernising a legacy risk system. It assumes you can read Python and reason about probability. It assumes nothing about insurance. Actuaries will find the mathematics stated precisely; engineers will find every formula that computes a number paired with the code that computes it.

Scope

Property-catastrophe reinsurance, after the model has run. Everything on this site starts from the catastrophe model’s loss output — thousands of simulated futures, each a trial in the vocabulary the Analytics Toolkit defines — and works downstream: how contracts transform loss, how portfolios aggregate it, and how prices and capital derive from it. The focus is deliberate: property cat is where losses are most extreme, where models matter most, and where the analytics are hardest to engineer.

Not covered, by design

The following topics are outside this site’s scope. Each is a discipline of its own with its own methods and literature — they sit either upstream of the cat model’s loss output or outside property catastrophe:

• Catastrophe-model internals — hazard, vulnerability, and event-generation modules. This site consumes the model’s loss output; it does not explain how the model produces it.
• Exposure rating and exposure curves — pricing from exposure profiles rather than model output.
• Experience rating — pricing from a cedent’s historical losses.
• Reserving and IBNR (incurred but not reported) — estimating liabilities for losses that have already occurred.
• Casualty, specialty, life, and health reinsurance — lines whose analytics rest on different foundations than simulated catastrophe output.

If a question sits upstream of the model’s loss output, or outside property cat, the question is out of scope here.

The scope statement defines the landscape this site explores. Other conventions — vocabulary, the sign convention, units, loss perspectives, capital — are indexed on one page, Scope, conventions & assumptions, each with a pointer to the section that explains it.

How the site is organised

Four chapters, in reading order, and three reference pages the chapters draw on throughout:

A single fictional reinsurer, Helios Re, runs through every chapter: six contracts, five cedents, and a 20-trial loss dataset small enough to check by hand. The numbers recur from page to page, so a figure you meet in the Toolkit is the same loss a contract transforms in Financial Modelling and a pricing story judges in Applications.

Foundations

Explore the structure of the reinsurance industry — its participants, how money and risk flow between them, and why contracts are the central mechanism of risk transfer.

Analytics Toolkit

Understand how reinsurers quantify risk using trial-based simulation, from exceedance probability curves to Value at Risk (VaR) and Tail Value at Risk (TVaR).

Financial Modelling

Learn how contracts transform loss — a small catalog of financial terms (loss filter, contract period, occurrence excess, aggregate excess, scaling) that composes into quota shares, catastrophe excess of loss (CatXoL) and aggregate excess of loss (AggXoL) contracts, programs, and portfolios.

Applications

See how the analytical tools combine to answer real business questions — profiling a cedent’s submission, pricing a program standalone, and rolling many contracts up into one portfolio. Marginal pricing with a portfolio view is (planned).