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 demons...
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 c...
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 acc...
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 structu...
Learn how Ledger unlocks steady, upfront cash flows and strong returns by letting investors participate directly in insurance through a capital-efficient trust model.
Ledger has developed a novel tail factor model that generalizes several other well-known tail factor models in the actuarial literature. The attached Excel file allows for practiti...
We share a series of blurry images and ask you, the reader, to make some predictions about those pictures. We then use this series of examples to illustrate the power and value of ...
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 ea...
When an insurance company issues a policy, the company knows the amount of premium it will receive, but it may not know for many years exactly how much it will cost to settle all o...
The core measure of an insurance company's performance is its loss ratio. We describe what loss ratios are, and how they tend to behave. We explore how loss ratios vary by line of ...
Ledger uses a strategy for forecasting casualty insurance loss ratios that is significantly different from traditional actuarial practice. We describe how Ledger's analytics team a...
We share a series of blurry images and ask you, the reader, to make some predictions about those pictures. We then use this series of examples to illustrate the power and value of ...
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 performanc...
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 to...
Ledger Investing does not use actuarial science to price risk. We explain why we don't, and provide an intuitive justification of our alternate method through an analogy to a fund ...
Property & casualty insurance includes a wide number of distinct insurance products with widely varying characteristics. We describe what, fundamentally, property & casualty insura...
We look at basic features of insurance companies by exploring statutory filings data. We see how many property & casualty insurance companies there are, and how insurance groups ar...
Ledger Investing does not use actuarial science to price risk. We explain why we don't, and provide an intuitive justification of our alternate method through an analogy to a fund ...
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...
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 to...
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 performanc...
This anthology is a collection of articles we've written on the property and casualty insurance industry. It covers basics of the property and casualty insurance space, analyses of...
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 ca...
Loss development modeling is typically conducted in two steps: one model to estimate the link ratios (age-to-age factors or loss development factors) from the main portion of the t...
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-grounde...
Many tail factor estimation methods in common usage revolve around fitting a parametric curve to age-to-age factors or link ratios. In this paper, we propose a new parametric curve...
Averaging predictions from multiple candidate inferential models frequently outperforms predictions from any given candidate model in isolation. Here, we introduce BayesBlend, the ...
