# Ledger Library ## Demo of Workbench: AI Work Environment for Reinsurance 🛠️ At the Casualty Actuarial Society Reinsurance Seminar on June 5, 2025, Ledger presented a live demo of Workbench, an AI-powered tool for reinsurance that is currently in development. This video demonstrates... ### Casualty ILS: The New Corporate Finance At the 2025 @CasualtyActuarialSociety Reinsurance Seminar, Samir Shah spoke about the rise of casualty insurance-linked securities (ILS) — and how it can serve as the new tool of corporate finance for (re)insurers, alongside equity and debt. He answered the question that's stumped many: "What about the tail risk?" It's a question that's prevented many from seeing how securitization can increase returns, reduce risk, and provide flexible capital to manage fluctuating needs in soft and hard markets. In the talk, he covers why conventional ideas about reinsurance not only don't apply to casualty ILS but are contrary to how you structure ILS and why you use it. As a tool of corporate finance, insurance securitization has the potential to fundamentally recapitalize the global insurance industry at trillion-dollar scale, just as securitization did for the credit markets. ### Casualty ILS Part 1: What is Casualty Insurance? Casualty insurance is a financial safeguard provided by insurance companies to individuals and businesses. It covers them against losses stemming from third-party claims due to accidents... ### Casualty ILS Part 2: Cash Flows of Casualty Insurance Ledger gives investors exposure to the full cash flow engine of casualty insurance—upfront premiums, long-tail claim payouts, investment income, and low-volatility risks—by structuring... ### Casualty ILS Part 3: Capital Investment in Casualty Insurance Learn how Ledger unlocks steady, upfront cash flows and strong returns by letting investors participate directly in insurance through a capital-efficient trust model. ### Loss Ratio Dynamics We rely on time series models for estimating the loss ratios insurers will achieve in future years. Our choice of models is not arbitrary or purely driven by backtesting performance... ### Casualty Insurance Lines of Business Property & casualty insurance includes a wide number of distinct insurance products with widely varying characteristics. We describe what, fundamentally, property & casualty insurance is about... ### Line of Business Volume and Diversification The US property & casualty industry is subdivided into 22 separate lines of business in Schedule P of the annual statements mandated by the NAIC. We explore the relative size of each... ### Prior Distributions for Link Ratios Many traditional loss development models center around the notion of link ratios. We describe the importance of prior distributions in the context of Bayesian modeling, and some of... ### Loss Ratio Volatility and Insurer Skill Many investors are interested in understanding just how volatile insurer loss ratios are, and how much of that volatility is intrinsic to the insurance environment. We present a tool... ### A Bayesian workflow for securitizing casualty insurance risk In this paper, we lay out our Bayesian workflow for securitizing casualty insurance-linked securities that uses: (1) theoretically informed time-series and state-space models to calculate... ### Improved Estimation of Parametric Tail Factor Models Loss development tail factors are difficult to estimate, due to training data that is typically quite sparse and volatile. We propose a new estimation technique that is well-grounded... ### BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging and Stacking in Python Averaging predictions from multiple candidate inferential models frequently outperforms predictions from any given candidate model in isolation. Here, we introduce BayesBlend, the ... ### Bermuda: A Python package for insurance loss triangles Bermuda is a Python package for the representation, manipulation, and exploration of insurance loss triangles, created by Korra. The code is fully open sourced at the Github repository... ### BayesBlend: A Python package for model blending and stacking BayesBlend is a Python package to facilitate the blending and stacking of stochastic (typically Bayesian) models. It is fully open sourced at the Github repository... ### LedgerAnalyticsAPI: A Python package for insurance loss modeling LedgerAnalyticsAPI is a Python package allowing access to our remote compute infrastructure for running state-of-the-art insurance loss models. Find out more at the Github Repository... [Casualty ILS: The New Corporate Finance](https://www.youtube.com/watch?v=hLMmwZj1us0) - YouTube