The Spectator insurance year book.

Mode of access: Internet.

Cyclopedia of insurance in the United States.

Issues for 1916- include section: Biographical sketches.

Office of Consumer Health Insurance annual report.

"Section 90(a)(7)(215 ILCS 134/90(a)(7))--requires OCHI to file an annual report with the Governor, the Director of Insurance, and the General Assembly."

Report of the Illinois Insurance Fraud Task Force.

"The Illinois Insurance Fraud Task Force was created by Public Act 91-522. The Act was signed into law by Governor Ryan on August 13, 1999"--Leaf 6.

Annual report of the Commissioner of Insurance of the State of Wisconsin.

Reports for 1895-1914 have each pt. issued as separate vol.: pt. 1. Fire and marine insurance; pt. 2. Life and casualty insurance; 1897-1915, pt. 3. Local mutual fire insurance.

Proceedings of the ... annual meeting of the National Board of Fire Underwriters.

Description based on: 1914.

The history of the National board of fire underwriters; fifty years of a civilizing force,

Mode of access: Internet.

Best's insurance reports : property-liability.

Mode of access: Internet.

The Spectator Insurance Year Book

Title varies: 1874-1937, The Insurance Year Book

Cyclopedia of insurance in the United States

Issues for 1916- include section: Biographical sketches

Proceedings of the annual meeting of the Fire Underwriters' Association of the Pacific

Mode of access: Internet.

Lectures delivered to the associate members of the Fire Underwriters' Association of the Pacific.

Mode of access: Internet.

Insurance map of Charleston, W. Va.

Shows outlines, location, and construction types of buildings.

A priori ratemaking using bivariate poisson regression models

In automobile insurance, it is useful to achieve a priori ratemaking by resorting to gene- ralized linear models, and here the Poisson regression model constitutes the most widely accepted basis. However, insurance companies distinguish between claims with or without bodily injuries, or claims with full or partial liability of the insured driver. This paper exa- mines an a priori ratemaking procedure when including two di®erent types of claim. When assuming independence between claim types, the premium can be obtained by summing the premiums for each type of guarantee and is dependent on the rating factors chosen. If the independence assumption is relaxed, then it is unclear as to how the tari® system might be a®ected. In order to answer this question, bivariate Poisson regression models, suitable for paired count data exhibiting correlation, are introduced. It is shown that the usual independence assumption is unrealistic here. These models are applied to an automobile insurance claims database containing 80,994 contracts belonging to a Spanish insurance company. Finally, the consequences for pure and loaded premiums when the independence assumption is relaxed by using a bivariate Poisson regression model are analysed.

Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.