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093044 (M52) Reinsurance contracts with a multi-year aggregate limit
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Abstracts and Reviews
creased understanding of that business is critical to continued success for both reinsurers and their clients. The purpose of this paper is to describe a framework for an integrated pricing and reserving process on a individual risk basis. Utilizing this framework, increasing levels of sophistication and knowledge can be brought to bear, risk by risk, on understanding a reinsurer's book of business.
This paper presents and compares five analytical formulas for the approximation of stop-loss premiums. Two of them, based on the inverse Gaussian distribution, are not widely known. The authors also suggest a technique which improves the precision of these approximations for portfolios.
Keywords: Stop-loss premiums, Inverse Gaussian distribution.
Keywords: Reinsurance, Pricing process, Reserving process. INSURANCE E C O N O M I C S
093044 (M52) Reinsurance Contracts with a Multi-Year Aggregate Limit Berens R.M., Casualty Actuarial Society, 1997, pp. 289-308. Excess of Loss reinsurance contracts commonly include an aggregate limit which specifies the maximum amount the reinsurer will pay under the contract. This paper discusses pricing implications of an aggregate limit which applies over multiple years. Monte Carlo simulations are used to test the sensitivity of the pricing to relationships between the average ground-up loss, the per-claim limit and the aggregate limit under the contract. A pricing example using historic data is also included. Risk charges and applications to clash covers are explored. Underwriting and reserving considerations of a contract with a multiyear aggregate are discussed. Keywords: Reinsurance, Monte carlo process, Multiyear aggregate limit. 093045 (M52) A Simulation Approach in Excess Reinsurance Pricing Papush D.E., Casualty Actuarial Society, 1997, pp. 330. This paper illustrates the application of a simulation method in excess reinsurance pricing. The author considers the simulation approach in computing aggregate loss distributions. The scope of the simulation method is more broad than for other aggregate loss distribution techniques. Keywords: Simulation, Reinsurance, aggregate loss.
093046 (M52) Some analytical approximations of stop-loss premiums Dufresne F., Niederhauser E., Bulletin de l'Association Suisse des Actuaires, Heft 1, 1997, pp. 25-47.
EIO: INSURANCE R E L A T E D M A T H E M A T I C A L ECONOMICS, G E N E R A L AND M I S C E L L A N E O U S
093047 (El0) Consumer Risk Perceptions and Information in Insurance Markets with Adverse Selection Ligon J.A, Thistle P.D., The Geneva Papers on Risk and Insurance Theory, Vol. 21, No 2, 1996, pp. 191210. Standard Models of adverse selection in insurance markets assume policyholders know their loss distributions. This study examines the nature of equilibrium and the equilibrium value of information in competitive insurance markets where consumers lack complete information regarding their loss probabilities. The authors show that additional private information is privately and socially valuable. When the equilibrium policies separate types, policyholders can deduce the underlying probabilities from the contracts, so it is information on risk type, rather than loss probability per se, that is valuable. They show that the equilibrium is "as if" policyholders were endowed with complete knowledge if, and only if, information is noiseless and costless. If information is noisy, the equilibrium depends on policyholders' prior beliefs and the amount of noise in the information they acquire. Keywords: Adverse selection, Hidden information, Informational equilibrium, Learning. 093048 (El0) Plausible Upper Bounds: Are their Sums Plausible? Cogliano V.J., Risk Analysis, Vol. 17, No.l, 1997, pp. 77-84. Quantitative cancer risk assessments are typically expressed as plausible upper bounds rather than estimates of central tendency. In analysis involving
Abstracts and Reviews
creased understanding of that business is critical to continued success for both reinsurers and their clients. The purpose of this paper is to describe a framework for an integrated pricing and reserving process on a individual risk basis. Utilizing this framework, increasing levels of sophistication and knowledge can be brought to bear, risk by risk, on understanding a reinsurer's book of business.
This paper presents and compares five analytical formulas for the approximation of stop-loss premiums. Two of them, based on the inverse Gaussian distribution, are not widely known. The authors also suggest a technique which improves the precision of these approximations for portfolios.
Keywords: Stop-loss premiums, Inverse Gaussian distribution.
Keywords: Reinsurance, Pricing process, Reserving process. INSURANCE E C O N O M I C S
093044 (M52) Reinsurance Contracts with a Multi-Year Aggregate Limit Berens R.M., Casualty Actuarial Society, 1997, pp. 289-308. Excess of Loss reinsurance contracts commonly include an aggregate limit which specifies the maximum amount the reinsurer will pay under the contract. This paper discusses pricing implications of an aggregate limit which applies over multiple years. Monte Carlo simulations are used to test the sensitivity of the pricing to relationships between the average ground-up loss, the per-claim limit and the aggregate limit under the contract. A pricing example using historic data is also included. Risk charges and applications to clash covers are explored. Underwriting and reserving considerations of a contract with a multiyear aggregate are discussed. Keywords: Reinsurance, Monte carlo process, Multiyear aggregate limit. 093045 (M52) A Simulation Approach in Excess Reinsurance Pricing Papush D.E., Casualty Actuarial Society, 1997, pp. 330. This paper illustrates the application of a simulation method in excess reinsurance pricing. The author considers the simulation approach in computing aggregate loss distributions. The scope of the simulation method is more broad than for other aggregate loss distribution techniques. Keywords: Simulation, Reinsurance, aggregate loss.
093046 (M52) Some analytical approximations of stop-loss premiums Dufresne F., Niederhauser E., Bulletin de l'Association Suisse des Actuaires, Heft 1, 1997, pp. 25-47.
EIO: INSURANCE R E L A T E D M A T H E M A T I C A L ECONOMICS, G E N E R A L AND M I S C E L L A N E O U S
093047 (El0) Consumer Risk Perceptions and Information in Insurance Markets with Adverse Selection Ligon J.A, Thistle P.D., The Geneva Papers on Risk and Insurance Theory, Vol. 21, No 2, 1996, pp. 191210. Standard Models of adverse selection in insurance markets assume policyholders know their loss distributions. This study examines the nature of equilibrium and the equilibrium value of information in competitive insurance markets where consumers lack complete information regarding their loss probabilities. The authors show that additional private information is privately and socially valuable. When the equilibrium policies separate types, policyholders can deduce the underlying probabilities from the contracts, so it is information on risk type, rather than loss probability per se, that is valuable. They show that the equilibrium is "as if" policyholders were endowed with complete knowledge if, and only if, information is noiseless and costless. If information is noisy, the equilibrium depends on policyholders' prior beliefs and the amount of noise in the information they acquire. Keywords: Adverse selection, Hidden information, Informational equilibrium, Learning. 093048 (El0) Plausible Upper Bounds: Are their Sums Plausible? Cogliano V.J., Risk Analysis, Vol. 17, No.l, 1997, pp. 77-84. Quantitative cancer risk assessments are typically expressed as plausible upper bounds rather than estimates of central tendency. In analysis involving