Description: Since health care reform has made accountable care organizations a hot topic, an SOA workgroup is addressing relevant questions, including provider risk under various ACO models, limitations of the Medicare model for motivating change in the health care delivery system, strategic priorities, attribution of members, meaurement, and the roles actuaries can play.

Description: This abstract describes a paper that considers a general risk model in which both the claim and income gain arrivals follow Poisson processes.

Description: Presented at August 2011 46th Actuarial Research Conference. This paper focuses on mainly focus on the case in which the risk variable follows a distribution function from a max-domain of attraction.

Description: This paper presents an algorithm for approximating the probability of ruin for a Poisson process - which is often used to model an aggregate claims process.

Description: From a session at the Spring meeting of the Society of Actuaries held in San Antonio, Texas, June 14-15, 2004 Speakers discuss the approaches to quantifying investment risk, including the credit risk subcomponent and mismatch risk sub-component in the three different types of risk-based capital RBC framework commonly used, such as regulatory, rating agency and company-specific economic-based formulas.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: The article provides a summary of the Drake Risk & Opportunity Forum held on October 21, 2022. The forum was a hybrid conference that attracted more than 200 attendees from 17 states, two countries, 48 employers, and five universities. Following an introduction by the Zimpleman College of Business Dean, the forum held six sessions. First was an insurance company CRO panel followed by a panel of non-insurance company CROs. Gary Zhu shared his outlook for interest rates and capital markets. The fourth panel discussed insurance capital models. The fifth panel discussed environmental, social, and governance (ESG) criteria when building insurance company investment portfolios. The final session of the day was a discussion about the NAIC, how they operate, and their priorities for the coming year.

Description: The initial risk reserves in collective risk models vary according to the underlying claim distribution, and a suitable level of ruin probability. A thorough analysis of the needed initial surplus for various ruin probability levels is provided in eight meaningful examples. The claim distributions are drawn from various fields of insurance, including property damage and liability insurance.

Description: Presented at October 1985 Annual Meeting. Discusses risk measurement and quantification, cash-flow-based surplus, factors that affect benchmark surplus, how multiple risks can be combined for benchmark surplus, benchmark surplus and the valuation actuary, and uses of benchmark surplus formulas.